{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calibrating a Network Using Mercury Intrusion Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mercury intrusion porosimetry (MIP) is a common technique in the study of porous media used to determine the pore size distribution of a porous material. There are two reasons why one would want to fit a PNM to MIP data.\n",
    "\n",
    "The first reason is to more accurately obtain pore size distributions from MIP data.  MIP data is universally interpreted using a 'bundle of tubes' model, which neglects the shielding effect that occurs when large pore bodies are 'shielded' behind smaller ones.  A more nuanced interpretation of MIP data requires using a pore network model to fit the data, then obtaining the pore and throat size distribution of the model. This is not usually done because it is quite a bit more difficult, and the additional accuracy is not necessarily justified. \n",
    "\n",
    "The second reason is that often we wish to generate a cubic pore network that is representative of a specific material so that we can then perform additional simulations using the network.  This is called *network calibration*.  Calibration can also involve fitting of permeability and formation factor data as well, since successfully fitting more metrics means a better calibration. \n",
    "\n",
    "In this example, we will show how OpenPNM can be used to simulate mercury intrusion and estimate the pore size distribution of a network, and we'll compare this experimental values, and iterate until they match. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import Packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 333,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import openpnm as op\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.stats as spst\n",
    "\n",
    "op.visualization.set_mpl_style()\n",
    "np.random.seed(10)\n",
    "ws = op.Workspace()\n",
    "ws.settings[\"loglevel\"] = 40\n",
    "np.set_printoptions(precision=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import Data for a Sandstone\n",
    "\n",
    "For this work we will use the porosimetry data from [Characterization of the pore structure of reservoir rocks with the aid\n",
    "of serial sectioning analysis, mercury porosimetry and network simulation\" by  Tsakiroglou and Payatakes in Advances in Water Resources 23 (2000) 773-789](http://doi.org/10.1016/S0309-1708(00)00002-6).  The data we extracted from Figure.8 in that paper using a graph digitizer:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's import the MIP data for this sample:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 334,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       Pc [Pa]     S_Hg\n",
      "0      12056.4  0.00122\n",
      "1      15162.4  0.00368\n",
      "2      17630.0  0.00741\n",
      "3      23693.0  0.00860\n",
      "4      30708.0  0.01607\n",
      "5      36799.0  0.01979\n",
      "6      44633.0  0.02351\n",
      "7      49752.0  0.02599\n",
      "8      52522.0  0.03474\n",
      "9      55439.0  0.05476\n",
      "10     55449.0  0.05473\n",
      "11     57820.0  0.06977\n",
      "12     59569.0  0.09980\n",
      "13     62089.0  0.16613\n",
      "14     63563.0  0.22244\n",
      "15     65092.0  0.25123\n",
      "16     66585.0  0.37262\n",
      "17     68232.0  0.34759\n",
      "18     69833.0  0.42518\n",
      "19     71069.0  0.47100\n",
      "20     71085.0  0.45271\n",
      "21     76355.0  0.54039\n",
      "22     76802.0  0.54156\n",
      "23    101289.0  0.60534\n",
      "24    117732.0  0.63785\n",
      "25    135188.0  0.67913\n",
      "26    160014.0  0.70663\n",
      "27    203630.0  0.73037\n",
      "28    222870.0  0.74787\n",
      "29    267020.0  0.76787\n",
      "30    348080.0  0.79660\n",
      "31    437710.0  0.80783\n",
      "32    696280.0  0.83528\n",
      "33   1148210.0  0.87899\n",
      "34   1860000.0  0.90268\n",
      "35   2352900.0  0.92016\n",
      "36   3975500.0  0.94885\n",
      "37   5214900.0  0.95882\n",
      "38   7353000.0  0.98253\n",
      "39   9821400.0  0.99375\n",
      "40  11698800.0  0.99622\n",
      "41  12884400.0  0.99620\n",
      "42  15440700.0  0.99617\n",
      "43  17108000.0  0.99865\n"
     ]
    }
   ],
   "source": [
    "df = pd.read_csv('Sandstone.csv')\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have 45 pressure points, and the mercury volume has already been normalized by the porosity, which was 18% in this case. \n",
    "\n",
    "Before we get into the network modeling, it is a good idea to convert the pressure data to pore size data using the bundle of tubes model to get a first approximation of the sizes to expect:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 335,
   "metadata": {},
   "outputs": [
    {
     "data": {
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Gjh2rTZs2VZjD3bZt26Y5c+aoc+fOCgkJUePGjRUeHq5Ro0bprbfeMp+x5+hcShZgkKR77723zBVsd+7cWW4OV69e1R//+EeNGDFCbdq0ka+vr4KDg3X//fdr7ty5OnjwYIXn8dJLL5nHKrkFPC8vTx9++KFGjhyptm3bysfHR15eXkpMTKzKW1Rttiv6Dh48uFL72L5nVYlJTEzUM888o06dOikgIEABAQHq06eP3nnnnTL/Pg8ePKhp06YpJiZG/v7+Cg0N1ZAhQ+xm6AIAUC8YAADAYwwaNMiQZEgyFi1aVGH8Cy+8YMY3atSo1OuXLl0yhg0bZsaU99OhQwfjwIEDDo8VGxtrxq9cudLYvXu30aZNmzL7y8zMtNv3+++/N3r06FFhHp06dTKOHTtWlbesXDt27LDru6rS0tIMHx8fc/958+aVGXf3+1KWlJQUIzQ0tMLzl2SEhoYa//jHPxzmlpSUZMZHRkYahYWFxvz58x32O336dKOoqMgwDMPIyckxHnvsMYfx//3f/12p9yklJcUYPHhwhecVHh5u7Nq1y+G5VOZnx44dZebx1ltvGUFBQQ739fLyMmbMmGHcunWr3PNZtGiR3d/g8ePHjc6dO5fZ33fffVep98iW7XU5aNAgy/apzLV/d8xrr71mNGzYsNz3b9SoUUZ+fr5hGIZRWFhoPPPMMw7f7yeffNIoLCysVL7VPU8AANwFizAAAFCHZWZmmu2goCC71y5duqT+/fvrzJkz5u/uu+8+9enTR40bN9bx48eVkJAgSTp16pSGDBmizZs3q3///hUe9/Tp05o/f75u3Lihpk2bauDAgQoPD1dmZqZ27dplF7tr1y49+uijunnzpqTi56316tVLHTp0UKNGjZScnKzdu3crPz9fP/74o/r166d9+/YpJiam2u+LM4SFhWnAgAHavn27pOLZZdWVk5Ojq1evSpKaNWumzp07KzIyUgEBAbp9+7aSkpK0f/9+5efn6+rVqxozZoy+/vpruxmOjvzmN7/Rm2++qQYNGqhXr166//77VVhYqG+++UbJycmSpJUrV6pDhw5auHChJk6cqE2bNsnb21v9+/dX+/btlZubqx07dig9PV2StGTJEvXs2VNPPvlkucf94YcfNGzYMKWlpUkqnlHVs2dP3X///fLz89PFixe1a9cuZWVlKTU1VSNGjNCmTZs0ZMgQs4/AwEBzhdqPP/5YWVlZkqSpU6eqadOmpY4ZERFR6nfz58/XsmXLzO3mzZurb9++CgsLU35+vr777jsdPXpUhmHoz3/+s1JTU/XVV1+pQQPHN4tcvXpVjzzyiFJSUuTr66sBAwYoMjJS2dnZ2r9/v8N9Pc2KFSu0cOFCSVK3bt3Uo0cPNWzYUAkJCTp+/Lik4pm08+bN04oVKxQXF6f333/fvOZiYmJUVFSkb775RklJSZKkNWvWqHv37nr++edddl4AANQaV1cAAQBA5VV1Bly3bt3M+F69etm9Nnr0aPM1f39/Y/Xq1aX2P3DggNGuXTszrk2bNqVmr5Wwnenl7e1tSDLmzp1rZGVl2cXdvn3buHPnjmEYxbPIWrZsae43depUIzU1tVTf6enpxoQJE8y4rl27VmnmTFlqOgPOMAzj17/+tbl/gwYNjNzc3FIxlZkBl5ycbPzyl780EhISzPfmbjdu3DAWLFhg9tWxY8dyY21njTVq1Mjw8vIyoqOjS83IKigosJsZ16xZM+Pll182JBkDBgwwzp49axefm5trTJ482Yxv166dOWvubtnZ2UZMTIwZO3r0aOP06dNlnpftTKl77rnHuH79epl9RkZGmnFJSUllxtztww8/NPcJDAw0/vSnPxm3b98uFbd9+3YjIiLCjH3ttdfK7M92BlzJdT5x4kTj8uXLdnF37twp8zgVcdcZcI0bNzbCwsLKnGH4+uuv270nS5cuNSQZMTExRmJiol3s3bMxAwICjOzsbMvOEwAAd0EBDgAAD1KVAtyXX35p9w/o559/3nxt+/btdq99+eWX5faTlJRkd+veyy+/XGacbaFJkvGf//mfFZ7PjBkzzPjybuEsUVhYaAwdOtSMX7NmTYX9O+KMAlx8fLxdHykpKaViKlOAq4o5c+aY/W3cuLHMmLtv22zRooWRlpZWZmxhYaHRqVMnu/iYmJgyi4mGYRg3b940QkJCzNiEhIQy4xYvXmzGTJgwodxiYQnb9+n3v/99mTFVLcDdvHnTCA4ONiQZPj4+xv79+x3GHz9+3PD19TWk4lt9c3JySsXYFuAkGSNHjqzw3KrCXQtwvr6+xtGjR8uNHT58uF18y5YtjUuXLpUZe/c1t3bt2krlTAEOAODJWIQBAIA66LPPPtPTTz9tbjdu3FhxcXHm9ooVK8z2T3/6U40dO7bcvqKiovTCCy+Y2++9916ZD+y35evrqz/84Q8OY65cuaK//OUvkopv53zttdccxjds2FCvvPKKue0OD3G/+7Ze21t+rTJ9+nSzXdmVbV944QWFhYWV+VrDhg01efJku9/97ne/k5+fX5nxTZs2tbte/vWvf5WKKSgo0FtvvSWp+Np77733Kryd89VXXzUf9u+sz/bPf/6zueBHXFyc+vTp4zA+JiZGsbGxkopvL928eXOFxyi5tbeumz17tjp37lzu61OmTLHbfuGFF9SyZcsyY+++5sq6hgAAqGt4BhwAAB5q48aNysjIsPvd9evX9a9//UunTp2y+/3SpUvVpk0bc3vHjh1me8aMGRUea/r06fr1r3+toqIipaWl6ccff1R0dHS58SNHjlSzZs0c9rl161bdvn1bkvT444/L19e3wjz69Okjf39/5eTkaPfu3RXGWy0gIMBuu+T5ZDVRUFCghIQEff/990pPT1dWVpbd6pK2x6jsKpsTJ050+HrXrl3Ntp+fn8aMGeMwvkuXLma75Hletg4ePKjLly9LkoYNG1ZuIcZWeHi4oqOj9cMPP+jo0aO6ceNGqQJnVW3cuNFsP/XUU5XaZ+jQoWaBevfu3Xr88cfLje3WrZvLn0VYW6pyDVUmvqJrCACAuoYCHAAAHurAgQM6cOCAw5imTZtq2bJldrOmLl68aBZHJFXqQf4tWrRQx44ddeLECUnSoUOHHBbgfvKTn1TY5759+8z24cOH9Ytf/KLCfWxlZmYqJydH/v7+VdrPme4uuAUGBla7r7y8PL366qt67733ShVWy1OZuKCgILVu3dphjG2xtGPHjmrUqJHD+JCQELNdsniGLdvP9sKFC5X+bEtmqxmGoQsXLtS4AGebx/vvv6+PPvqown0uXLhgts+fP+8wtjLXeV1hWzAri+01FBQUVOZiGLYquoYAAKhrKMABAFCHBAQEKDQ0VN26ddPw4cM1depUBQcH28VcuXLFbPv5+alFixaV6jsqKsoswFVU+KlMn6mpqWZ79+7d1ZrRlpmZ6dIC3I0bN+y2bYsKVZGZmamhQ4dWekZbicrMuKtMEcvb+99fCasaX1BQUOp128/28OHDOnz4cIV93q2mt/NmZ2fbvT8ffPCB03Oo7N9OXVDRdeHsawgAgLqGAhwAAB5q0aJFeumll6q8X3Z2ttmuSvHKNraiwk95zw+zdXfxqjpsb810hZKCpFT8XKvmzZtXq5+5c+eaxTcfHx9NnTpVjz76qGJiYnTPPffIz89PDRs2lCQlJyfr3nvvlSQVFRVV2HfJc9Uqq6rxZXGHz7Y2cqjMdV5XVOW6cMY1BABAXUMBDgCAesb2uWU5OTmV3s82tmnTpjXOw7agt3TpUj377LM17rO2JSQkmO0HHnhAjRs3rnIfFy9e1Jo1ayRJDRo00ObNmzVkyJBy453xnDmr2X628+bN07Jly1yagyRdu3atwucS1heVKdwCAADnqvtLNgEAADu2t83l5eVV+nljycnJZru6M71stWrVymynp6fXuL/alpaWpj179pjbAwcOrFY/27dvN1eVHT16tMPimySdO3euWsepTe7w2QYHB9sVRD3xGqss22f2VWbmoDNmBwIAgKqhAAcAQD0TERFhtyrl3r17K9wnIyNDJ0+eNLd79uxZ4zz69Oljtm0LWZ5i+fLlds+uevLJJ6vVj+3z0u5eSbIsu3btqtZxapPtZ7t3716zwFhTVb21sXfv3mbbE6+xyrJd/OPq1asVxh85csTKdAAAQBkowAEAUA/ZzrKKj4+vMD4+Pt68bS08PFydOnWqcQ6jRo0yH8S+d+9eff/99zXus7bs3btXS5YsMbdHjhypXr16VauvBg3+/XUsNzfXYWxubq4+/vjjah2nNvXv399c/OPChQvasGGDU/r19fU125V5cP+4cePM9rvvvuu0QqC7iYyMNIuTp0+ftnvOY1nWrVtXG2kBAAAbFOAAAKiHZs+ebbbXr1+vLVu2lBt77tw5vfLKK3b7OuMh6xEREXr66aclSYZhaOrUqbp582al9i0qKrJbzbU2bd68WY8++qh5q5+/v79dMa6q2rVrZ7Y3btyoO3fulBu7YMECXbp0qdrHqi2NGzfW/Pnzze24uDhdvHix0vuXd46hoaFmuzL9zZ492ywEHjp0SC+//HKlc8jIyHD4WbiTwMBARUdHSyq+BXXVqlXlxn733Xf605/+VFupAQCA/48CHAAA9dCQIUM0evRoc3vixIn69NNPS8V9++23Gj58uK5fvy5JatOmjebNm+e0PF555RXdc889kqTDhw+rd+/e+sc//lFu/IULF/TGG2+oU6dOWrt2rdPyqEhhYaG+/vprPfHEExo7dqyuXbsmqXj22qpVq9StW7dq9z106FA1adJEUvHspdjYWPP9LnHz5k3NmjVL7733XpVWrnWlBQsWqHPnzpKKi2UPPvigPv3003IXAMjIyND777+vnj17llvQ7NKli9ku63q9W1BQkN544w1z++WXX1ZsbKxSUlLKjDcMQ3v27FFcXJzatm2rvLy8Co/hLp566imz/fzzz2v37t2lYjZt2qSRI0eySikAAC7AKqgAANRTK1euVP/+/XXmzBllZ2dr8uTJ6tChg/r06SMfHx8dP35cCQkJ5m17/v7+Wr16tTmjyBnCw8P1+eefa8yYMcrIyNCPP/6oUaNGKSIiQr1791aLFi1UUFCgjIwMHT16VElJSU479t1+8Ytf2G3n5+fr+vXrSk9P16FDh0oVY9q0aaP4+HgNHTq0Rsdt1qyZfvWrX2nx4sWSpFWrVmnTpk3q06ePIiIilJaWpp07dyonJ0fe3t565513FBsbW6Nj1oaAgAB98cUXGj58uJKSkpSenq7JkyerefPmeuihhxQWFibDMHTt2jUdP35cp06dMotz5b2nTzzxhFasWCFJeuedd/Ttt9+qZ8+eZgFTkp555hndd9995va0adN09uxZ/fa3v5Ukffzxx1q1apV69Oih6OhoBQQEKDs7WxcuXFBiYqLHLlDwy1/+Uu+++65SU1N1/fp1DRw4UP3791d0dLTy8/N18OBBnThxQlLxLeXTpk1zbcIAANQzFOAAAKinWrVqpT179uipp57S9u3bJUmnTp3SqVOnSsW2b99en3zySbWfc+ZIr169dPDgQc2cOVPbtm2TVDxjav369Q5z79Chg1PzePvttysV17p1a82cOVPz5893WjHyxRdfVHJysvl8t2vXrmnTpk12McHBwVq5cqV69OjhlGPWhnbt2ungwYOaM2eO/vrXv8owDGVkZOjLL78sd5/g4OByF6MYMWKEpkyZotWrV0uSEhISlJCQYBczbtw4uwKcJC1evFhdunTRs88+q9TUVN25c0fffvutvv3223Lz6N27t93qou4uKChIGzZs0KhRo5SRkSHDMLR79267mXA+Pj564403FBsbSwEOAIBaRgEOAIB6rFWrVtq2bZs2b96stWvXavfu3UpPT1dBQYFatmypBx54QOPHj9fTTz9taTEiMjJSW7du1b59+/Tpp59q165dOn/+vDIzM+Xt7a3Q0FB16NBBDz74oEaOHKnBgwebCzhYwcvLSwEBAQoKClJQUJA6deqkn/zkJ3rooYc0aNAgNWzY0KnHa9iwoT766CNNmjRJ77//vhISEpSZmalmzZqpbdu2euyxxzRjxgyFh4crOTnZqce2WkhIiNatW6ejR49q9erV2rlzp5KSknT16lU1aNBAwcHBat++vXr27Knhw4drxIgRdost3G3VqlUaN26cVq9ercTERGVkZCg/P7/CPCZPnqzHHntMa9as0ZYtW3TgwAFduXJF2dnZ8vf3V0REhGJiYvTwww9rzJgx6tixozPfhlrRs2dPnThxQkuXLtWGDRuUlJSkoqIitW7dWiNGjFBcXJzuv/9+V6cJAEC95GXU1eWgAAAAAA+zc+dOc5XiQYMGaefOna5NyI3w3gAAPBmLMAAAAAAAAAAWogAHAAAAuKGvv/5aXl5e5s/48eNdnVKtSk5Otjv/ktlvAAB4IgpwAAAAAAAAgIVYhAEAAABwExEREZo7d26Zr3Xv3r2Ws3GtwMDAct8LZ6+CDACA1ViEAQAAAAAAALAQt6ACAAAAAAAAFqIABwAAAAAAAFiIAhwAAAAAAABgIQpwAAAAAAAAgIUowAEAAAAAAAAWogAHAAAAAAAAWIgCHAAAAAAAAGAhCnAAAAAAAACAhSjAAQAAAAAAABaiAAcAAAAAAABYiAIcAAAAAAAAYCEKcAAAAAAAAICFKMABAAAAAAAAFqIABwAAAAAAAFiIAhwAAAAAAABgIQpwAAAAAAAAgIUowAEAAAAAAAAWogAHAAAAAAAAWIgCHAAAAAAAAGCh/wdteDr1qSTs8AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 463,
       "width": 624
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['R'] = -2*0.480*np.cos(np.deg2rad(140))/df['Pc [Pa]']\n",
    "fig, ax = plt.subplots()\n",
    "ax.semilogx(2*df['R']*1e6, df['S_Hg'], 'b.')\n",
    "ax.set_xlabel('Pore Diameter [um]');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that we should aim to have pore diameters in the range of 20-30 um.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Network"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We may want to use a large network for some future simulations, but for the sake of the fitting process we can use a relatively small network to get the parameters.  Here we will use use a simple cubic network with 15 pores per side and a spacing of 40 um.  Note that we *can adjust* this spacing if it let's us match the data more closely."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 336,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "══════════════════════════════════════════════════════════════════════════════\n",
      "net : <openpnm.network.Cubic at 0x2315ad6f220>\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "  #  Properties                                                   Valid Values\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "  2  pore.coords                                                   3375 / 3375\n",
      "  3  throat.conns                                                  9450 / 9450\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "  #  Labels                                                 Assigned Locations\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "  2  pore.surface                                                         1178\n",
      "  3  throat.surface                                                       2352\n",
      "  4  pore.left                                                             225\n",
      "  5  pore.right                                                            225\n",
      "  6  pore.front                                                            225\n",
      "  7  pore.back                                                             225\n",
      "  8  pore.bottom                                                           225\n",
      "  9  pore.top                                                              225\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n"
     ]
    }
   ],
   "source": [
    "pn = op.network.Cubic(shape=[15, 15, 15], spacing=30e-6)\n",
    "print(pn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add Geometrical Properties\n",
    "\n",
    "The network object only contains topological and spatial information.  We need to assign some pore and throat sizes.  Since one of the objectives of this tutorial is to shine some light on the use of pore-scale models and how to customize them, we will *not* use the convenient pre-packages model collections, but instead add all the models we need by hand.  Let's start by assigning sizes to the pore bodies:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pore Sizes\n",
    "\n",
    "It is possible to produce sizes directly from a statistical distribution, like ``scipy.stats.weibull_min.rvs(<args>)``, however, we are going to do it the \"hard way\" since this will help us later.  We'll start by assigning random seed values between 0 and 1 to the network:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 337,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(0)  # Set the state of the random number generator to \"0\"\n",
    "pn['pore.seed'] = np.random.rand(pn.Np)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's define a statistical distribution. The Weibull distribution is common since it has mostly small pore and a long tail of a few large pores, which is typical of many porous materials."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 338,
   "metadata": {},
   "outputs": [],
   "source": [
    "dst = spst.weibull_min(c=1.9, loc=1e-7, scale=20e-6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above line creates what is called a \"frozen object\", meaning that `dst` is now a `weibull_min` object with the parameters `c`, `loc`, and `scale` fixed at their given values. \n",
    "\n",
    "Let's quickly look at some values from this distribution to see if the parameters we chose are a decent starting point. The `rvs` method returns the requested number of randomly generated values from the frozen distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 339,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 464,
       "width": 623
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.hist(dst.rvs(10000)*1e6, bins=50, edgecolor='k')\n",
    "ax.tick_params(axis='x', labelrotation=45)\n",
    "ax.set_xlabel('Pore Diameter [um]');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This looks pretty good.  The minimum value (`loc`) was set to 100 nm, and the `scale` of 20 um positions the distribution well within our expected range.  Lastly, the `c` value controls the skew, which has created a slightly elongated tail, but nothing too  extreme.  Only a few values will be larger than the network spacing of 40 um, which we will revisit later."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Finding Pore Sizes Given Random Seeds between 0 and 1\n",
    "Before moving on, let's first examine how we can produce random values given seed values between 0 and 1.  Below is a plot of the cumulative probability distribution (`cdf`). The y-axis is the `pn['pore.seed']` values, and the x-axis is the pore size value.  The `'pore.seed'` values are chosen at random between 0 and 1, and the size values can be found by doing a reverse \"look-up\", shown by the red lines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 340,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 463,
       "width": 623
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(dst.ppf(pn['pore.seed']), pn['pore.seed'], 'b.')\n",
    "ax.plot([0, dst.ppf(0.5), dst.ppf(0.5)], [0.5, 0.5, 0.0], 'r-')\n",
    "ax.tick_params(axis='x', labelrotation=45);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are two important advantages to this approach.\n",
    "\n",
    "Firstly, we can limit the range of seed values, for instance from 0.1 to 0.9, which will prevent any abnormally large values that might occur if a point far out on the tail end of the distribution is chosen (like 0.9999).  \n",
    "\n",
    "Secondly, this simplifies the process of creating spatially correlated pore sizes since there are many way to generate correlated random numbers between 0 and 1 (i.e. `porespy.generators.fractal_noise`). We won't go into that here, but it was used to create anisotropic networks in [this work](https://doi.org/10.1016/j.jpowsour.2007.04.059)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Apply Distribution to the Network\n",
    "\n",
    "We can now use this model to generate our pore sizes for the network.  We can do this easy way or the right way.  \n",
    "\n",
    "First the easy way: Let's just assign values from the frozen distribution to the network directly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 341,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 463,
       "width": 623
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pn['pore.diameter'] = dst.rvs(pn.Np)\n",
    "fig, ax = plt.subplots()\n",
    "ax.hist(pn['pore.diameter']*1e6, edgecolor='k')\n",
    "ax.tick_params(axis='x', labelrotation=45)\n",
    "ax.set_xlabel('Pore Diameter [um]');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The problem with this approach is that if we were to change the values of 'pore.seed', it would have no effect on the pore sizes.  This is not really an issue in the current example since we haven't used a model for 'pore.seed' values. However, a common use case might be to re-run a simulation N times to ensure the results are repeatable. If a model for 'pore.seed' were used, then we could just do `pn.regenerate_models()`, and OpenPNM would generate a new set of 'pore.seed' values, then it would recompute all the values that depend on 'pore.seed', starting with 'pore.diameter', and then 'pore.volume', and so forth.\n",
    "\n",
    "To properly leverage the OpenPNM models regeneration features, we need to assign the statistical model (ie. 'weibull_min') to the network as a pore-scale model. OpenPNM includes a `generic_distribution` function, which accepts a pre-initialized `scipy.stats` distribution, like the one we defined above.  Let's also add a model for 'pore.seed' values, and truncate the values in the range of [0.0 to 0.98]."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 342,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JdT0Nyll014goWb+yrqcBALDHsggDAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGSoYV1PAAD2JCUb10RExNKlS6Nz5851OxkqWLp0aV1PAQAAakUABwDlJUlERJSWlsbixYvreDIAAMC+QAAHAJXJyY0GzVrX9Swop2T9yrqeAgAA1IoADgAq0aBZ6+h82eS6ngblfDD+lIiktK6nAQAAO80iDAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZyjyAmzRpUuTk5OzUfxdeeGGN68+YMSOGDx8e3bp1i2bNmkWbNm2id+/eMWrUqJg/f36t5jxv3rwYNWpU9O7dO9q0aRPNmjWLbt26xYgRI2LGjBm1qgkAAABA/dSwridQW2vXro2RI0fGtGnTKuzfuHFjrF69OubOnRt33HFHjB07Nq6++uoa173pppti7NixUVxcXGH/O++8E++880488MADMWzYsJgwYUK0aNFil7wWAAAAAPZduzWA69GjRwwePLjafv3799/h48XFxXH66afHzJkz0329evWKPn36RFFRUbzwwguxdOnSKC4ujmuuuSaKi4vj+uuvr/Z5r7/++rjhhhvS7U6dOsWxxx4b+fn5MWfOnHjrrbciImLq1KmxcuXKeOKJJ6Jhw702wwQAAABgN9it6dF//Md/xM9//vNPXOeGG25Iw7f8/Py4//77Y+jQoenjmzdvjmuvvTZ+/OMfR0TEmDFjYsCAATFgwIAqa86YMaNC+DZq1Ki48cYbIy8vL903derUOP/886OoqCimT58eP/rRj2oU7AEAAABQf+11izAsX748fvKTn6Tbt99+e4XwLSIiLy8vxo8fH2eddVZERCRJUu3XUMs/PnTo0Bg/fnyF8C0iYtiwYfHTn/403b711lvj448/rvVrAQAAAGDft9cFcJMnT44NGzZERES3bt1i5MiRVfYdP3585OZufYmzZs2K119/vdJ+r7zySrzyyisREZGbmxvjx4+vsubFF18cn/nMZyIiYt26dTFlypRavQ4AAAAA6oe9LoB79NFH0/a5554bOTk5Vfbt2rVrDBo0KN1+5JFHqq05ZMiQ6NKlS5U1c3JyYsSIEdXWBAAAAICIvSyAKyoqitmzZ6fbAwcOrHbM8ccfn7bLL9pQ3jPPPFPrmi+99FJs2rSp2jEAAAAA1E+7dRGGNWvWxG9+85t466234l//+lfst99+ccABB0S/fv3i8MMP3+HVbBERCxYsiNLS0ojYeiXaEUccUe1z9unTJ23Pmzev0j7l95fvX5Xyz1tSUhJvv/12HH744dWOq0xBQUH069evVmNnzZpVq3EAAAAA+6ra5iwFBQW7eCb/tlsDuMceeywee+yxSh/7zGc+E9///vfj/PPPrzKIW7BgQdru0KFD5OfnV/ucXbt2TdurVq2KFStWRPv27dN9y5cvjzVr1qTbBx10ULU1mzRpEu3bt48VK1ZERMT8+fNrHcCtX7++wlV9AAAAANTenpiz7DFfQX3nnXfiwgsvjFNOOSVdZGFbK1euTNv7779/jep27NixwvaqVauqrFnbutvWBAAAAIAyuyWA69q1a3z3u9+NJ598Mj788MMoKiqKDRs2xIIFC+IXv/hF9OjRI+37hz/8Ic4+++z0q6blrV+/Pm03adKkRs+9bb/yNSrbrk3dbWsAAAAAQJnMA7jTTjst/vnPf8att94aX/rSl6Jz587RuHHjaNq0aXTr1i0uueSS+Nvf/hbnnXdeOubxxx+PX/3qV9vVKioqStt5eXk1ev7GjRtX2C4sLKyyZm3rblsTAAAAAMpkfg+4Vq1aVdsnLy8vJk6cGP/4xz/ihRdeiIiIW265Jc4555wK/crf823z5s01ev5tVyjd9gq3be8jt3nz5hrdW6583ZpeNVeZ5s2bR69evWo9HgAAAIB/O+aYY2o1rqCgILNvOe7WRRh2JDc3N374wx/GkCFDImLri160aFF07tw57dO8efO0XdOrzrbtV75GZduFhYU1CuDK1922xs7o1auX1UwBAAAAdpHa5iz9+vXLbAGHPWYRhoiI4447Lho1apRuz5s3r8Ljbdu2TdsfffRRjWouW7aswnabNm2qrFnbutvWBAAAAIAye1QA16hRo2jXrl26/fHHH1d4vHv37ml7+fLl292/rTILFy5M223atIn27dtXeLxDhw4Vvib7wQcfVFuzqKgoVqxYkW6XX0QCAAAAAMrbowK4iIgNGzak7WbNmlV4rHv37pGbu3XKSZLEG2+8UW291157LW337Nmz0j7l97/++us7VbNBgwbRrVu3ascAAAAAUD/tUQHce++9F2vXrk23DzjggAqP5+fnV7iR3rPPPlttzeeeey5tDxo0qNI+xx9/fK1r9u/ff7uVVgEAAACgzB4VwN13331pu2XLlvH5z39+uz6nnXZa2p40adIO63344YcxY8aMSsdWVfPpp5+ORYsW7bBu+eetqiYAAAAARGQcwO3M0q0vvfRS3Hbbben20KFDo2HD7RdpHTFiRPrV1AULFsTEiROrrPn9738/SkpKImLrShZ9+vSptF/fvn2jb9++ERFRUlISo0ePrrLmvffeG2+//XZERLRo0SKGDx9ezSsDAAAAoD7LNID77W9/G0cffXQ88MAD8a9//avSPkVFRXHnnXfGkCFD0kUVWrVqFT/84Q8r7d+hQ4e46qqr0u3LL788HnrooQp9iouLY/To0TF16tR0380337zDuZZ//MEHH4zRo0dHcXFxhT4PPfRQXHnllen29773vQqLRgAAAADAtra/xGwXe+WVV2LEiBHRsGHD6NGjR/To0SNat24dJSUlsXjx4pg1a1aF+741adIkHnvssejUqVOVNa+77rp48cUXY+bMmVFYWBhnnXVW3HjjjdGnT58oKiqK559/PpYuXZr2Hzt2bAwYMGCH8xw8eHBce+21ceONN0ZExC233BJTpkyJY489NvLz82POnDlRUFCQ9j/hhBPimmuuqe0fCwAAAAD1ROYBXJktW7ZEQUFBhRBrW0cffXRMmjSpytVKyzRq1CgefvjhGDlyZHr129y5c2Pu3Lnb9RszZkyNg7Jx48ZF48aNY9y4cVFcXBxLliyJadOmbddv6NChMWHChEq/IgsAAAAA5WWaIA0bNiy6desWL730UsyePTvefffd+Pjjj2PlypVRWloaLVu2jIMPPjiOOeaY+OpXvxr/+Z//WePaLVu2jGnTpsVFF10UkydPjlmzZsXSpUujUaNG0aVLlzjxxBPjggsuqDbMKy8nJyeuvfbaOPPMM2PixIkxffr0+PDDD6O4uDg6deoU/fr1ixEjRsSQIUNq88cBAAAAQD2UaQDXuHHj6N+/f/Tv3z+z5xgyZMguD8R69uxZYUEIAAAAAKitTBdhAAAAAID6TgAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGSoYV1PAMjGUUcdFcuWLavraVCJpUuX1vUUAAAA2I0EcLCPWrZsWSxevLiupwEAAAD1ngAO9nU5udGgWeu6ngXllKxfWddTAAAAYDcSwME+rkGz1tH5ssl1PQ3K+WD8KRFJaV1PAwAAgN3EIgwAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhuo8gLvqqqsiJycn/e9Tn/rUTo2fMWNGDB8+PLp16xbNmjWLNm3aRO/evWPUqFExf/78Ws1p3rx5MWrUqOjdu3e0adMmmjVrFt26dYsRI0bEjBkzalUTAAAAgPqpTldBffnll+OOO+6o1di1a9fGyJEjY9q0aRX2b9y4MVavXh1z586NO+64I8aOHRtXX311jevedNNNMXbs2CguLq6w/5133ol33nknHnjggRg2bFhMmDAhWrRoUau5AwAAAFB/1FkAV1xcHBdeeGGUlpbWauzpp58eM2fOTPf16tUr+vTpE0VFRfHCCy/E0qVLo7i4OK655pooLi6O66+/vtq6119/fdxwww3pdqdOneLYY4+N/Pz8mDNnTrz11lsRETF16tRYuXJlPPHEE9GwYZ1mmAAAAADs4ersK6i33HJLzJ07NyIizj777J0ae8MNN6ThW35+fkydOjXmzp0bkydPjmnTpsX7778fo0aNSvuPGTMmnnvuuR3WnDFjRoXwbdSoUfH+++/HtGnTYvLkyVFQUBC/+tWvIj8/PyIipk+fHj/60Y92at4AAAAA1D91EsDNnz8/brzxxoiI+MY3vhEnnHBCjccuX748fvKTn6Tbt99+ewwdOrRCn7y8vBg/fnycddZZERGRJEm1X0Mt//jQoUNj/PjxkZeXV6HPsGHD4qc//Wm6feutt8bHH39c47kDAAAAUP/s9gAuSZK48MILY9OmTdG6desKYVpNTJ48OTZs2BAREd26dYuRI0dW2Xf8+PGRm7v1Jc6aNStef/31Svu98sor8corr0RERG5ubowfP77KmhdffHF85jOfiYiIdevWxZQpU3Zq/gAAAADUL7s9gLv77rvjxRdfjIiIH//4x9GhQ4edGv/oo4+m7XPPPTdycnKq7Nu1a9cYNGhQuv3II49UW3PIkCHRpUuXKmvm5OTEiBEjqq0JAAAAABG7OYD78MMPY/To0RERceyxx8b555+/U+OLiopi9uzZ6fbAgQOrHXP88cen7fKLNpT3zDPP1LrmSy+9FJs2bap2DAAAAAD1025dwvPSSy+NdevWRV5eXkyYMGGHV69VZsGCBemqqTk5OXHEEUdUO6ZPnz5pe968eZX2Kb+/fP+qlH/ekpKSePvtt+Pwww+vdlxlCgoKol+/frUaO2vWrFqNAwAAANhX1TZnKSgo2MUz+bfdFsD9+te/jj/84Q8REfH9738/evbsudM1FixYkLY7dOiQrki6I127dk3bq1atihUrVkT79u3TfcuXL481a9ak2wcddFC1NZs0aRLt27ePFStWRMTWRSVqG8CtX7++wlV9AAAAANTenpiz7JavoK5cuTIuv/zyiNi6cMIPfvCDWtcps//++9doTMeOHStsr1q1qsqata27bU0AAAAAKLNbArjvfOc76dVi99xzTzRu3LhWddavX5+2mzRpUqMx2/YrX6Oy7drU3bYGAAAAAJTJPICbPn16TJkyJSIiRowYUWEBg51VVFSUtvPy8mo0Ztuwr7CwsMqata27bU0AAAAAKJPpPeA2bNgQF198cUREtG3bNm699dZPVK/8Pd82b95cozHbrlC67RVu295HbvPmzTW6t1z5ujW9aq4yzZs3j169etV6PAAAAAD/dswxx9RqXEFBQWbfcsw0gPvBD34Q77//fkRE3HbbbdGuXbtPVK958+Zpu6ZXnW3br3yNyrYLCwtrFMCVr7ttjZ3Rq1cvq5kCAAAA7CK1zVn69euX2QIOmX0F9bXXXouf/exnERFx/PHHx4gRIz5xzbZt26btjz76qEZjli1bVmG7TZs2Vdasbd1tawIAAABAmcyugHvzzTejtLQ0IiIWLly4w8v/yhZoiIhYunRphb7XXXddfPnLX46IiO7du6f7ly9fHkVFRdVerbZw4cK03aZNm2jfvn2Fxzt06BCtWrWKNWvWRETEBx98ED169NhhzaKiogpzrq4/AAAAAPVXpl9BLfPuu+/Gu+++W6O+mzdvjr/+9a/pdvmgq3v37pGbmxulpaWRJEm88cYb1X6v97XXXkvbPXv2rLRPz54908sTX3/99TjxxBNrXLNBgwbRrVu3HfYHAAAAoP7KfBXUXSk/P79C4Pbss89WO+a5555L24MGDaq0T/mVWXe2Zv/+/bdbaRUAAAAAymQWwJ177rmRJEmN/rv//vvTcQcddFCFx84999wKdU877bS0PWnSpB3O4cMPP4wZM2ZUOraqmk8//XQsWrRoh3XLP29VNQEAAAAgYi+7Ai4iYsSIEdGsWbOIiFiwYEFMnDixyr7f//73o6SkJCK2rmTRp0+fSvv17ds3+vbtGxERJSUlMXr06Cpr3nvvvfH2229HRESLFi1i+PDhtXodAAAAANQPe10A16FDh7jqqqvS7csvvzweeuihCn2Ki4tj9OjRMXXq1HTfzTffvMO65R9/8MEHY/To0VFcXFyhz0MPPRRXXnlluv29730v2rVrV5uXAQAAAEA9sVsWYdjVrrvuunjxxRdj5syZUVhYGGeddVbceOON0adPnygqKornn38+li5dmvYfO3ZsDBgwYIc1Bw8eHNdee23ceOONERFxyy23xJQpU+LYY4+N/Pz8mDNnThQUFKT9TzjhhLjmmmuyeYEAAAAA7DP2ygCuUaNG8fDDD8fIkSPTq9/mzp0bc+fO3a7fmDFjahyUjRs3Lho3bhzjxo2L4uLiWLJkSUybNm27fkOHDo0JEyZEw4Z75R8fAAAAALvRXpsgtWzZMqZNmxYXXXRRTJ48OWbNmhVLly6NRo0aRZcuXeLEE0+MCy64IHr27Fnjmjk5OXHttdfGmWeeGRMnTozp06fHhx9+GMXFxdGpU6fo169fjBgxIoYMGZLhKwMA2LuUbFwTERFLly6Nzp071+1kqFTHjh3j1VdfretpAEC9tUcEcOeee+52q53W1JAhQ3Z5INazZ8+47bbbdmlNAIB9VpJERERpaWksXry4jicDALDn2SMCOAAA9gE5udGgWeu6ngXllGxYHZGU1vU0AKDeE8ABALBLNGjWOjpfNrmup0E5i+4aESXrV9b1NACg3sut6wkAAAAAwL5MAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGGmb9BB9//HG8+OKL8fLLL8fcuXPj3XffjSVLlsT69eujUaNG0bp16+jVq1cMHDgwhg8fHgceeOBO1Z8xY0ZMnjw5Zs+eHYsXL47GjRtH586d48QTT4wLLrggevTosdNznjdvXtx3333xpz/9KRYtWhSbNm2KAw88MPr16xfDhw+PwYMH73RNAAAAAOqnzAO4c889N5544olKH9uyZUsUFhbGkiVLYvr06TF27Ni4+uqr47rrrovc3B1fnLd27doYOXJkTJs2rcL+jRs3xurVq2Pu3Llxxx13pDVr6qabboqxY8dGcXFxhf3vvPNOvPPOO/HAAw/EsGHDYsKECdGiRYsa1wUAAACgfso8gCuvXbt20bNnzzjooIOiefPmsXHjxvjHP/4RL7/8cmzZsiU2bdoUY8aMiffeey8mT55cZZ3i4uI4/fTTY+bMmem+Xr16RZ8+faKoqCheeOGFWLp0aRQXF8c111wTxcXFcf3111c7v+uvvz5uuOGGdLtTp05x7LHHRn5+fsyZMyfeeuutiIiYOnVqrFy5Mp544olo2HC3/hECAAAAsJfJPD0aOHBgfOUrX4nBgwfHpz/96Ur7fPTRR/Gd73wnpk6dGhERDzzwQHzlK1+Jr371q5X2v+GGG9LwLT8/P+6///4YOnRo+vjmzZvj2muvjR//+McRETFmzJgYMGBADBgwoMp5zpgxo0L4NmrUqLjxxhsjLy8v3Td16tQ4//zzo6ioKKZPnx4/+tGPahTsAQAAAFB/Zb4Iw/e+9724+OKLqwzfIiL233//ePDBB2PQoEHpvgkTJlTad/ny5fGTn/wk3b799tsrhG8REXl5eTF+/Pg466yzIiIiSZJqv4Za/vGhQ4fG+PHjK4RvERHDhg2Ln/70p+n2rbfeGh9//PEO6wIAAABQv+0xq6Dm5OTEeeedl26//vrrlfabPHlybNiwISIiunXrFiNHjqyy5vjx49N7yc2aNavKmq+88kq88sorERGRm5sb48ePr7LmxRdfHJ/5zGciImLdunUxZcqUHbwqAAAAAOq7PSaAi4ho37592l63bl2lfR599NG0fe6550ZOTk6V9bp27VrhqrpHHnmk2ppDhgyJLl26VFkzJycnRowYUW1NAAAAAIjYwwK4v//972n7U5/61HaPFxUVxezZs9PtgQMHVlvz+OOPT9vlF20o75lnnql1zZdeeik2bdpU7RgAAAAA6qc9ZgnPJUuWxK233ppuV7YAw4IFC6K0tDQitl6JdsQRR1Rbt0+fPml73rx5lfYpv798/6qUf96SkpJ4++234/DDD692XGUKCgqiX79+tRo7a9asWo0DAAAA2FfVNmcpKCjYxTP5tzoN4DZu3Bjvv/9+/PGPf4zx48fH8uXLIyKiZ8+eMXr06O36L1iwIG136NAh8vPzq32Orl27pu1Vq1bFihUrKnzVdfny5bFmzZp0+6CDDqq2ZpMmTaJ9+/axYsWKiIiYP39+rQO49evXV7iqDwAAAIDa2xNzlt0awP3lL3+JY489dod9TjrppHjwwQejRYsW2z22cuXKtL3//vvX6Dk7duxYYXvVqlUVArjyNXe2blkAt2rVqhqNAQAAAKD+2WPuAde6deuYOnVqPPHEE9GqVatK+6xfvz5tN2nSpEZ1t+1XvkZl27Wpu20NAAAAACizW6+AO+CAA+Kyyy6LiIgkSWLdunWxYMGCeO2112L16tUxbNiwuPfee+Oee+6Jbt26bTe+qKgobefl5dXoORs3blxhu7CwsMqata27bU0AAAAAKLNbA7hDDjkkfv7zn2+3f8mSJfGDH/wgJk2aFM8880wcc8wx8eyzz0bv3r0r9Ct/z7fNmzfX6Dm3XaF02yvctr2P3ObNm2t0b7nydWt61VxlmjdvHr169ar1eAAAAAD+7ZhjjqnVuIKCgsy+5bhHrIJ6wAEHxP333x/77bdf3HnnnbF69eoYOnRozJ07Nxo0aJD2a968edqu6VVn2/YrX6Oy7cLCwhoFcOXrbltjZ/Tq1ctqpgAAZKJk45qIiFi6dGl07ty5bidDpTp27BivvvpqXU8DYJ9S25ylX79+mS3gsEcEcGVuvvnmmDRpUqxduzbmzZsXf/zjH+Pkk09OH2/btm3a/uijj2pUc9myZRW227RpU2G7fM2yuq1bt96putvWBACAPUKSREREaWlpLF68uI4nAwD11x4VwDVt2jT69+8fTz31VEREvPjiixUCuO7du6ft5cuXR1FRUbVXqy1cuDBtt2nTpsIKqBERHTp0iFatWsWaNWsiIuKDDz6IHj167LBmUVFRugJqRFTbHwAA6lRObjRoVv0vmdl9SjasjkhK63oaAOwme1QAFxEVrj5buXJlhce6d+8eubm5UVpaGkmSxBtvvFHt93pfe+21tN2zZ89K+/Ts2TO9PPH111+PE088scY1GzRoUOmCEQAAsKdo0Kx1dL5scl1Pg3IW3TUiStavrL4jAPuE3LqewLaWLl2atrf9amd+fn6FwO3ZZ5+ttt5zzz2XtgcNGlRpn+OPP77WNfv377/dSqsAAAAAUGaPCuBWrlxZ4UZ5lV2xdtppp6XtSZMm7bDehx9+GDNmzKh0bFU1n3766Vi0aNEO65Z/3qpqAgAAAEBExgHcqlWraty3tLQ0/vu//zs2bdoUERGNGzeucP+3MiNGjIhmzZpFRMSCBQti4sSJVdb8/ve/HyUlJRGxdSWLPn36VNqvb9++0bdv34iIKCkpidGjR1dZ895774233347IiJatGgRw4cPr8GrAwAAAKC+yjSAe+CBB6Jv377xwAMPxNq1a6vs9+abb8ZJJ50Uv/71r9N9o0aN2m6F0oitiyZcddVV6fbll18eDz30UIU+xcXFMXr06Jg6dWq67+abb97hXMs//uCDD8bo0aOjuLi4Qp+HHnoorrzyynT7e9/7XrRr126HdQEAAACo3zJfhOHVV1+NESNGRMOGDaNHjx7RvXv3aN26deTk5MTKlSvjzTffjH/84x8Vxpx55pnxwx/+sMqa1113Xbz44osxc+bMKCwsjLPOOituvPHG6NOnTxQVFcXzzz9f4V5yY8eOjQEDBuxwnoMHD45rr702brzxxoiIuOWWW2LKlClx7LHHRn5+fsyZMycKCgrS/ieccEJcc801tfkjAQAAAKAeyTSAK784wZYtW6KgoKBCiLWtFi1axJgxY+KKK66IBg0aVNmvUaNG8fDDD8fIkSPTq9/mzp0bc+fO3a7fmDFjahyUjRs3Lho3bhzjxo2L4uLiWLJkSUybNm27fkOHDo0JEyZEw4Z73CKyAAAAAOxhMk2QLrnkkhg8eHA8/fTT8de//jXeeuutWLhwYaxZsyYiIvbbb7/o1KlTfP7zn48hQ4bEmWeeGc2bN69R7ZYtW8a0adPioosuismTJ8esWbNi6dKl0ahRo+jSpUuceOKJccEFF1S6kENVcnJy4tprr40zzzwzJk6cGNOnT48PP/wwiouLo1OnTtGvX78YMWJEDBkypDZ/HAAAAADUQ5lfwtWtW7fo1q1bXHrppZnUHzJkyC4PxHr27Bm33XbbLq0JAAAAQP2U6SIMAAAAAFDfCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDAjgAAAAAyJAADgAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDAjgAAAAAyJAADgAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDAjgAAAAAyJAADgAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDAjgAAAAAyJAADgAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDAjgAAAAAyJAADgAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDAjgAAAAAyJAADgAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDAjgAAAAAyJAADgAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDAjgAAAAAyJAADgAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDmQdw77//fvzf//1fnHPOOfG5z30uWrduHY0aNYo2bdpE79694+KLL47nnnuuVrVfeeWVuPTSS+Owww6L/fbbL/bbb7847LDD4tJLL41XXnmlVjUXLlwYY8aMiSOPPDLat28fTZo0iUMPPTS++tWvxiOPPBJJktSqLgAAAAD1U8OsCr/++uvxrW99K15++eVKH1+9enWsXr065s6dG/fee28MHDgwJk+eHF27dq229ubNm2PUqFHxs5/9bLtAbN68eTFv3ry455574oorrojx48dHo0aNajTnX/7yl3HFFVfEhg0bKux/77334r333ovf/e53MWTIkJgyZUp07NixRjUBAAAAqN8yC+AWLFiwXfjWrVu36NWrV7Rr1y7WrFkTL730UixatCgiIp599tno169fvPDCC3HIIYfssPZFF10UDzzwQLp9yCGHxDHHHBMREbNnz4733nsvkiSJ22+/PdauXRu//OUvq53vfffdFxdeeGG63apVqxg0aFC0bNkyCgoK0ivqnn766TjxxBPjxRdfjObNm9fsDwMAAACAeiuzAK7Mpz/96bjwwgvjnHPOiQMPPLDCY6WlpTFp0qT49re/HRs3bowlS5bEN77xjXjppZciJyen0nr33XdfGr7l5ubGbbfdFpdffnnk5uamNe+888747ne/G6WlpXHffffFgAEDYvjw4VXOccGCBfGtb30r3f7GN74REyZMiGbNmqX7Zs6cGV/96ldj9erV8eabb8bll18e9913X63/XAAAAACoHzIL4Dp16hT3339/fPOb34wGDRpU2ic3NzfOP//8aN26dZxxxhkRsfUKtunTp8eJJ564Xf9NmzbFmDFj0u3/+Z//iSuvvHK7mldeeWUsW7YsbrnlloiIuP7662Po0KGRl5dX6Tyuu+66KC4ujoiIL3zhC/HAAw+kgV6ZQYMGxYMPPhgnnXRSREQ88MADMWrUqOjZs2f1fxgAAADllGxcExERS5cujc6dO9ftZKhUx44d49VXX63raQD7iMwCuAEDBsSAAQNq1Pf000+Po48+Ov3K6hNPPFFpAPf444/Hhx9+GBERLVu2jOuuu67Kmtdff33cfffdsXbt2vjggw/iiSeeiNNPP327fh999FH87ne/S7fHjx+/XfhW5ktf+lIMGTIknn766SgpKYl77rkn7rjjjhq9RgAAgNT/u5d1aWlpLF68uI4nA0DWMv8Kak194QtfSAO4999/v9I+jz76aNo+66yzomnTplXWa9q0aXz961+PiRMnRkTEI488UmkA9/jjj0dpaWlEbL1HXf/+/Xc4z3PPPTeefvrpdD4COAAAoNZycqNBs9Z1PQvKKdmwOiIpretpAPuYPSaAK3/Pt5KSkkr7PPPMM2l74MCB1dY8/vjj0wBu5syZu6xmmYULF8Y//vGP+PSnP13tOAAAgG01aNY6Ol82ua6nQTmL7hoRJetX1vU0gH3MHhPAzZ07N2136dJlu8f/9a9/xdKlS9PtPn36VFuzfJ/FixfH2rVrY7/99qvQZ968eTtV84ADDoj9998/Pvroo3T8JwngCgoKol+/frUaO2vWrFo/LwAAAMC+qLY5S0FBwS6eyb/tEQHcwoULK1yhNmTIkO36LFiwoMJ2165dq627bZ8FCxZE3759q6x70EEH1Wi+Xbt2TQO4+fPnx1e+8pUajavM+vXrY/bs2bUeDwAAAMC/7Yk5yx4RwF111VXp1067du1aaaC1cuW/LwHeb7/9okmTJtXWbdq0abRo0SLWrVsXERGrVq2q8HhhYWEUFham2/vvv3+N5tuxY8e0vW3N+uaoo46KZcuW1fU0qET5K0YBAACAulPnAdzkyZMrrEJ68803R+PGjbfrt379+rRdk/CtfN+yAK58jcq2a1q3fL9ta9Q3y5Yts2oTAAAAwA7UaQD36quvxre+9a10e9iwYXH22WdX2reoqCht5+Xl1fg5yod55a9227bmztTdUc16y+pNexw3jgUAAIA9Q50FcP/85z/jK1/5ShqC9e7dO+65554q++fn56ftzZs31/h5Nm3alLa3vcKtfM2dqbujmjurefPm0atXr09UY09g9aY9zwfjT7F8OgAAAPXOMcccU6txBQUFmX3TsU4CuKVLl8YJJ5yQ3jvskEMOiaeeemq7FUrLa968edremavOyvctX6Oy7ZrW3VHNndWrVy+rmQIAAADsIrXNWfr165fZAg65mVTdgZUrV8YJJ5wQ7777bkREdOrUKZ5++uno1KnTDse1bds2ba9du3a7r49WZuPGjen93yIi2rRpU+HxJk2aVLiCrWxl0+qUX3Rg25oAAAAAUN5uDeDWrl0bJ554Yrz11lsREdGuXbt4+umn4+CDD652bPfu3Stsf/DBB9WOWbhw4Q5rbLuvJjW3rdujR48ajQEAAACgftptAdyGDRvipJNOijlz5kRERMuWLeOpp56Kww47rEbjW7ZsWeEquddff73aMa+99lraPvDAAyv9imvPnj13quaSJUsqXClXfjwAAAAAbGu3BHBFRUVxyimnxIsvvhgREU2bNo0nnngijjzyyJ2qc/zxx6ftZ599ttr+zz33XNoeNGjQLq/ZtWvX+PSnP13tGAAAAADqr8wDuOLi4jjzzDNj5syZERHRuHHjeOyxx+ILX/jCTtc67bTT0va0adN2uGhCYWFhPPTQQ5WOLe+UU06J3NytfwwLFiyo9mZ7kyZNStunnnpq9ZMGAAAAoF7LNIArKSmJs88+O5588smIiGjYsGE89NBDMWTIkFrVO+WUU6Jz584REbFmzZq46aabqux7ww03xJo1ayIi4qCDDoqTTz650n77779/nHHGGen2//zP/0SSJJX2nT59ekyfPj0iIho0aBDf+ta3avMyAAAAAKhHMgvgkiSJCy64IH77299ufaLc3JgyZUqccsopta7ZuHHjGDt2bLp98803x5133hmlpaXpvtLS0rjzzjvjlltuSfeNGzcu8vLyqqx7ww03RKNGjSIi4oUXXogRI0bEhg0bKvR55pln4uyzz063hw8fXuP71wEAAABQfzXMqvDdd98dkydPTrcPPfTQ+Mtf/hJ/+ctfajT+5z//eaX7zz///Hj22WdjypQpUVpaGldccUXceeedccwxx0RExOzZs+Pdd99N+5933nkxfPjwHT5Xjx494u67744LL7wwIiKmTJkSf/jDH2LQoEGx3377xd///vf461//mvbv3bt33HHHHTV6HQAAAADUb5kFcMuXL6+w/c4778Q777xT4/FVBXARERMnToyWLVvGXXfdFUmSxLvvvlshdIuIyMnJiW9/+9tx66231uj5LrjggkiSJK688srYsGFDrF69On73u99t12/w4MExZcqUaNGiRY1fCwAAAAD1V2YBXJby8vLiZz/7WXzzm9+M++67L5599tlYvHhxREQceOCBMXDgwLjggguib9++O1X3wgsvjC9+8Yvxy1/+Mn7/+9/HwoULY/369dGpU6fo06dPnHPOOXHaaadFTk5OFi8LAAAAgH1QZgHcmDFjYsyYMVmVj4iIo48+Oo4++uhdWrNr164xduzYCveaAwAAAIDaynQVVAAAAACo7wRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZEsABAAAAQIYEcAAAAACQIQEcAAAAAGRIAAcAAAAAGRLAAQAAAECGBHAAAAAAkCEBHAAAAABkSAAHAAAAABkSwAEAAABAhgRwAAAAAJAhARwAAAAAZEgABwAAAAAZaljXEwAAAIA9RcnGNRERsXTp0ujcuXPdToZKdezYMV599dW6ngbsFAEcAAAAlEmSiIgoLS2NxYsX1/FkgH2FAA4AAAC2lZMbDZq1rutZUE7JhtURSWldTwNqRQAHAAAA22jQrHV0vmxyXU+DchbdNSJK1q+s62lArViEAQAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADK0WwK4kpKSePPNN+OXv/xlXHLJJXHUUUdFXl5e5OTkRE5OTgwcOLDWtWfMmBHDhw+Pbt26RbNmzaJNmzbRu3fvGDVqVMyfP79WNefNmxejRo2K3r17R5s2baJZs2bRrVu3GDFiRMyYMaPWcwUAAACg/mmY9RM8+uij8Y1vfCM2bty4S+uuXbs2Ro4cGdOmTauwf+PGjbF69eqYO3du3HHHHTF27Ni4+uqra1z3pptuirFjx0ZxcXGF/e+8806888478cADD8SwYcNiwoQJ0aJFi13yWgAAAADYd2UewK1Zs2aXh2/FxcVx+umnx8yZM9N9vXr1ij59+kRRUVG88MILsXTp0iguLo5rrrkmiouL4/rrr6+27vXXXx833HBDut2pU6c49thjIz8/P+bMmRNvvfVWRERMnTo1Vq5cGU888UQ0bJj5HyEAAAAAe7Hddg+4/fffP04++eQYO3ZsPPnkk3HFFVfUutYNN9yQhm/5+fkxderUmDt3bkyePDmmTZsW77//fowaNSrtP2bMmHjuued2WHPGjBkVwrdRo0bF+++/H9OmTYvJkydHQUFB/OpXv4r8/PyIiJg+fXr86Ec/qvVrAAAAAKB+yPzyrf/6r/+KDz74ILp27Vph/1//+tda1Vu+fHn85Cc/Sbdvv/32GDp0aIU+eXl5MX78+Fi4cGFMmzYtkiSJq6++Ol566aUq65b/murQoUNj/Pjx2/UZNmxY/Otf/4pLLrkkIiJuvfXWuPTSS6Ndu3a1ei0AAAAA7PsyvwKuY8eO24Vvn8TkyZNjw4YNERHRrVu3GDlyZJV9x48fH7m5W1/irFmz4vXXX6+03yuvvBKvvPJKRETk5uZWGr6Vufjii+Mzn/lMRESsW7cupkyZUqvXAQAAAED9sNu+grqrPProo2n73HPPjZycnCr7du3aNQYNGpRuP/LII9XWHDJkSHTp0qXKmjk5OTFixIhqawIAAABAxF4WwBUVFcXs2bPT7YEDB1Y75vjjj0/b5RdtKO+ZZ56pdc2XXnopNm3aVO0YAAAAAOqnvWoJzwULFkRpaWlEbL0S7Ygjjqh2TJ8+fdL2vHnzKu1Tfn/5/lUp/7wlJSXx9ttvx+GHH17tuMoUFBREv379ajV21qxZtRoHAAAAsK+qbc5SUFCwi2fyb3tdAFemQ4cO6YqkO1L+/nOrVq2KFStWRPv27dN9y5cvjzVr1qTbBx10ULU1mzRpEu3bt48VK1ZERMT8+fNrHcCtX7++wlV9AAAAANTenpiz7FVfQV25cmXa3n///Ws0pmPHjhW2V61aVWXN2tbdtiYAAAAAlNmrArj169en7SZNmtRozLb9yteobLs2dbetAQAAAABl9qoArqioKG3n5eXVaEzjxo0rbBcWFlZZs7Z1t60JAAAAAGX2qnvAlb/n2+bNm2s0ZtsVSre9wm3b+8ht3ry5RveWK1+3plfNVaZ58+bRq1evWo8HAAAA4N+OOeaYWo0rKCjI7FuOe1UA17x587Rd06vOtu1XvkZl24WFhTUK4MrX3bbGzujVq5fVTAEAAAB2kdrmLP369ctsAYe96iuobdu2TdsfffRRjcYsW7aswnabNm2qrFnbutvWBAAAAIAye1UA171797S9fPny7e7fVpmFCxem7TZt2kT79u0rPN6hQ4do1apVuv3BBx9UW7OoqChWrFiRbvfo0aPaMQAAAADUT3tdAJebu3XKSZLEG2+8Ue2Y1157LW337Nmz0j7l97/++us7VbNBgwbRrVu3ascAAAAAUD/tVQFcfn5+hRvpPfvss9WOee6559L2oEGDKu1z/PHH17pm//79t1tpFQAAAADK7FUBXETEaaedlrYnTZq0w74ffvhhzJgxo9KxVdV8+umnY9GiRTusW/55q6oJAAAAABF7YQA3YsSIaNasWURELFiwICZOnFhl3+9///tRUlISEVtXsujTp0+l/fr27Rt9+/aNiIiSkpIYPXp0lTXvvffeePvttyMiokWLFjF8+PBavQ4AAAAA6oe9LoDr0KFDXHXVVen25ZdfHg899FCFPsXFxTF69OiYOnVquu/mm2/eYd3yjz/44IMxevToKC4urtDnoYceiiuvvDLd/t73vhft2rWrzcsAAAAAoJ5ouDue5KSTToolS5ZU2Lds2bK0/eqrr8bnP//57cY9+eSTccABB2y3/7rrrosXX3wxZs6cGYWFhXHWWWfFjTfeGH369ImioqJ4/vnnY+nSpWn/sWPHxoABA3Y4x8GDB8e1114bN954Y0RE3HLLLTFlypQ49thjIz8/P+bMmRMFBQVp/xNOOCGuueaaGr1+AAAAAOqv3RLA/f3vf48PPvigysc3bNgQf/vb37bbv3nz5kr7N2rUKB5++OEYOXJkevXb3LlzY+7cudv1GzNmTI2DsnHjxkXjxo1j3LhxUVxcHEuWLIlp06Zt12/o0KExYcKEaNhwt/zxAQAAALAX22sTpJYtW8a0adPioosuismTJ8esWbNi6dKl0ahRo+jSpUuceOKJccEFF0TPnj1rXDMnJyeuvfbaOPPMM2PixIkxffr0+PDDD6O4uDg6deoU/fr1ixEjRsSQIUMyfGUAAADAtko2romIiKVLl0bnzp3rdjJUqmPHjvHqq6/W9TT2SLslgHv//fczqz1kyJBdHoj17Nkzbrvttl1aEwAAAPgEkiQiIkpLS2Px4sV1PBnYOXvtFXAAAABAPZSTGw2ata7rWVBOyYbVEUlpXU9jjyaAAwAAAPYaDZq1js6XTa7raVDOortGRMn6lXU9jT1abl1PAAAAAAD2ZQI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDAjgAAAAAyJAADgAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDAjgAAAAAyJAADgAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDAjgAAAAAyJAADgAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDAjgAAAAAyJAADgAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDAjgAAAAAyJAADgAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDAjgAAAAAyJAADgAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDAjgAAAAAyJAADgAAAAAyJIADAAAAgAwJ4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCOAAAAADIkAAOAAAAADIkgAMAAACADAngAAAAACBDDet6AtSNfv36xezZsyvsO+aYY2LWrFl1NCN2p6VTvhublyyosC/vgO7R6Zu31dGM2F0c+/rN8a+/HHtK1q+MD245Od12/OsH7/36zfGvvxz7PZMr4AAAAAAgQwI4AAAAAMiQAA4AAAAAMiSAAwAAAIAMCeAAAAAAIEMCuEps3rw5pkyZEieddFIcdNBBkZ+fH506dYr+/fvHrbfeGh9//HFdTxEAAACAvUTDup7Anmb+/PkxbNiweOONNyrsX7ZsWSxbtixmzZoVP/7xj+P++++Pk046qW4mCQAAAMBeQwBXzqJFi2Lw4MGxZMmSiIjIycmJ4447Lg499NBYsWJFPP3001FYWBjLly+P0047LZ566qkYNGhQHc8aAAAAgD2ZAK6cs88+Ow3fDjrooHjsscfic5/7XPr4xx9/HEOHDo0ZM2ZEcXFxfO1rX4t33303WrVqVUczBgAAAGBP5x5w/8+TTz4ZL7zwQkRE5OXlxe9///sK4VtERLt27eKxxx6LQw45JCIiVq1aFePHj9/tcwUAAABg7yGA+3/uuuuutD1ixIg4/PDDK+3XrFmzGDduXLo9YcKE2LJlS+bzAwAAAGDvJICLiPXr18eMGTPS7fPOO2+H/c8888xo3rx5RGy9Cu7555/PdH4AAAAA7L0EcBHx0ksvxaZNmyJi6xVuffv23WH//Pz86NevX7o9c+bMTOcHAAAAwN4rJ0mSpK4nUdfuuOOOuPLKKyMi4phjjolZs2ZVO2b06NFxyy23RETEGWecEb/73e+qHbP//vvH8uXLK+zLzc2Npk2b7vykI6JXr161GhcRUVBQEOvXr6+wr3nz5jtdc86cOVFcXByR2zDyOh5a6/mw621esmBro5JjU7zig0iKiyrsy2mUH43aH7S7plev7ejYZM2xr15dHp+s7e3Hf18+NlnL+tg7Nnuu9NhsY2967++rdsf7Zm//uV9X9pWfafvi8d9Xjk3W6uLYb172bkTplmjUqFEceeSRmT1PTRUUFNRq3MaNG6O0tLTCvg4dOsRHH330ieckgIuISy+9NO6+++6IiDjrrLPi17/+dbVjfvGLX8Rll10WERGHHXZYvPXWW9WOadGixXahFwAAAAB7pubNm8e6des+cR1fQY2IlStXpu3999+/RmM6duyYtletWrXL5wQAAADAvkEAF1HhqrQmTZrUaEz5fq5qAwAAAKAqAriIKCr693ej8/LyajSmcePGabuwsHCXzwkAAACAfUPDup7AniA/Pz9tb968uUZjylZNjaj5VXMHHnhgLF68OCK23tgvYusiDOWff2d8kkUYAAAAAPZFtV2EoaioKF2EoWzBzAMPPHCXzEkAF1tvqFemplezle9XfvyOzJ8/f+cmBgAAAMBez1dQI6Jt27Zpu6ZLyy5btixtt2nTZpfPCQAAAIB9gwAuIrp37562P/jggxqNWbhwYdru0aPHLp8TAAAAAPsGAVxE9OzZM23PnTs3tmzZUu2Y1157rdLxAAAAAFCeAC4i+vfvn65qumHDhnj11Vd32H/Tpk0xe/bsdHvQoEGZzg8AAACAvZcALrYuojB48OB0e9KkSTvs//DDD8e6desiYuv934477rgspwcAAADAXkwA9/9ceumlaXvSpEnx1ltvVdpv48aNcf3116fbI0eOjIYNLSYLAAAAQOVykiRJ6noSe4rjjjsuXnjhhYiI+NSnPhWPPfZY9O7dO3185cqVMWzYsPjzn/8cEVuvfnv33XejVatWdTFdAAAAAPYCArhyFi1aFEcffXQsXbo0IiJycnJiwIABceihh8aKFSvi6aefjo0bN0ZERMOGDeOpp56q8NVVAAAAANiWAG4b8+fPj2HDhsUbb7xRZZ/27dvH/fffH1/+8pd338QAAAAA2CsJ4CqxefPm+PWvfx1Tp06Nt956Kz766KNo1apVHHLIIXHGGWfEeeedF+3atavraQIAAACwFxDAAQAAAECGrIIKAAAAABkSwAGVcnEsANQfpaWldT0FoA4454fdRwAHpGbNmhVPPPFERGxdBRioPzZt2hQRTsTrs7Jj7+9A/TFz5syYNGlSRETk5vpnAdQXzvnrp6o+38t+AePzP3sN63oC7B1KS0udmO3jHn/88TjttNPiiCOOiP322y+OPfbYup4Su1GSJE7A6rE//elP8eijj8YPfvCD6Ny5c11PhzpS9jOg7P8++/dtZZ/7bdq0iTZt2sQpp5xS11NiD+G9v29zzl9/FRYWxvr162POnDmxcePGaN26dfTo0SOaN28e++23X/r5798F2RHAERERixYtisWLF8fvfve7WLt2bbRq1Spat24dQ4YMiZ49e0bTpk3reopk6Pe//32cdtppEbH1KpjFixc7+apncnJyorS0NAoLCyM3NzdycnIiPz8/fdzfh33X73//+zj11FMjNzc3OnfuHFdeeWU0a9asrqfFbvD+++/Hu+++G7/+9a9j7dq10bhx4+jYsWN84QtfiOOOOy5at25d11MkI+U/9/fff//46KOPoqSkJBo0aFC3E2O3cN5ffznnr79eeuml+OUvfxkzZ86MDz74IN3fqlWrOPLII+Ob3/xmfO1rX4smTZpETk6OEC4jVkElnn322Rg3blzMnz8/li1bVuGxTp06xYEHHhjjx4+Pnj17xv77719HsyQrZf/4jog47LDD4hvf+EZcccUVTr7qkbfeeiv++te/xuTJk2PNmjWxefPmaNiwYQwbNix69OgRZ5xxRtrXh/G+pfz7/5BDDokrrrgivvWtb0WjRo3qeGZkbebMmXHdddfFu+++G8uXL6/wWLNmzaJjx47xwx/+MPr27Rvdu3evo1mShW0/988555y4/PLLfe7XE8776y/n/PXXU089Feedd16sWrUqiouLo1GjRlFcXJwGbWXOOuusOOWUU2LYsGER4RfwWRDA1XNPPvlkDBs2LNatWxcREY0bN46If98LqEy7du3i1FNPjfPPPz/69eu32+dJNsp/EPfo0SPOPffc+O///u9o2rSpoKWemDFjRlx++eWxdOnSWLNmTTRo0CBKSkoiIqJhw4axZcuW+OY3vxnnnHNOHHvssZGfn+/DeB9R/v3fs2fPGDFiRPr+Z9/25JNPxte+9rUoLCyMiK2BW4MGDWLDhg3p+z9i62/FjzrqqPjOd74TX/rSl+pquuxCPvfrN+f99Zf3fv01Y8aMOPHEE6O0tDSaN28eBx98cAwcODDy8vJi1qxZsWjRoli4cGHav1u3bnHqqafGLbfcEhFCuF1NAFePPf/88/HlL385NmzYEAceeGB87nOfi29/+9uRl5cXb7zxRrz99tsxYcKEtH+TJk3ikEMOiTFjxsSZZ54ZEa6G2Zv5IOaPf/xjnHrqqbFly5aIiGjdunU0a9YsNmzYEEVFRek/ziMiPvvZz8bJJ58co0ePjpYtW/ow3svt6P3v2O7b/vKXv8TJJ58ca9euja5du8aRRx4Z3/ve96JJkyYxf/78ePvtt+MnP/lJFBYWRnFxcTRs2DDy8/Pj9ttvj/PPP7+up88n4HO/fnPeX39579df8+bNi6FDh8bcuXPj4IMPjnPOOSdGjRoVzZs3j4iINWvWxNq1a+Oqq66K2bNnx5IlSyJi66I8X//61+NXv/pVRAjhdqmEemnRokXJCSeckOTk5CQHHHBAMnbs2ORf//rXdv1mzJiRfPGLX0zatm2b5OTkJDk5OUmzZs2SKVOmpH1KS0t359TZBR5//PH0ePbs2TO55ZZbkg0bNiRJUvXx3LJlS9p2zPd+s2bNSjp16pTk5OQkhx56aHLxxRcnS5cuTVatWpUsW7YsefTRR5Mzzjgjyc3NTf+utGjRIvniF7+YfPzxx0mSVPw7wd6jNu9/9g0fffRRcuqppya5ublJhw4dqvzsf/nll5ORI0cmBx54YPp3JScnJ7njjjvqYNbsCrV535eUlKRtPxv2bs776y/n/PVT2XG77777klatWiU5OTnJRRddlKxfvz5JkiQpLi5OkuTfP+c3b96c3HvvvcnAgQMrfO5/+ctfTmuW/0yg9gRw9dTs2bOTjh07pm+sdevWJUlS+cnWO++8k4wbNy7p0qVLhTfkxIkT62TufDKPPfZYhQ/im2++udIP4pr8kBXA7H1KS0uTDRs2JBdddFHSuHHjpEWLFsm1116brF27NkmSrR/A5d15553bfRgfddRRyfLly5Mk8WG8t9nZE/HS0tL0GJeUlDgR38u9+eabafA+ePDg9NiXHePyx3fp0qXJ5MmTk8985jMV3v8333xzncyd2iv/uX/YYYf53K+HnPfXT7vynN/53t5pyJAhSU5OTtKqVavk/fffT5Jk+2NZ/jzv2WefTc4666wK7/2TTz55u77UngCunvre976X5OTkJHl5ecmf/vSnJEl2fFL18ccfJw8++GBy6KGHVnhDlv+NGHu+3/72t+mxO/jgg5Pbb799uw/ibf+BPXPmzOS+++5LRowYkVx88cXJmDFjkieffDI9eWPvs2LFiuTTn/50kpOTk/Tu3TtZs2ZNkiQVP1TL/zx47rnnkvPOO6/Ce79Hjx5CuL1M+fDts5/9bJUn4tv+DCjrU/Zb06r6secqO1Y/+tGPkpycnKRRo0bJr371qyRJ/v1b8Mps2rQpefHFF5PPfvazFd7/d955526ZN5/cb37zm/S4HXTQQcmdd96ZbNy4MUmSqj/3f//73ye33357ctJJJyWnnXZactlllyV33313smrVqt0+f3YN5/31j3N+SkpKkiOOOCJp2LBh0qZNm2TJkiVVnrOX/7vw97//PRkxYkSF9/7ZZ59daV92XsO6/gosdWPjxo0REVFcXBybN2+OiNjh97rbtm0bp59+erRo0SK++93vxj/+8Y+IiLjkkkuiWbNmcfrpp2c/aT6RhQsXxuWXXx4RW+/r0aRJkzj88MPT+z9E/PveHsXFxVFQUBATJkyISZMmpX9HyjRv3jwOOeSQuPvuu+OII46I/Pz83f56qL1XX3013n333cjJyYnBgwdXek+3Bg0apH8fjjvuuDjwwAOjbdu2cdttt0VExIIFC+LLX/5y/PGPf4y2bdu6N8Qe7rHHHkt/Tnfo0CG+/vWvx+jRoyPi3/f1KDveZfeCuf/+++O1116LmTNnRqNGjaKkpCS++MUvxhFHHBHnnHOOe8bsRcqOVdl9Hbds2RIbNmyIiK3v9ark5eVF//79Y+rUqXHOOefE3LlzIyLiiiuuiObNm8d5552X8cz5JD7++OO4+uqrI2Lr5/7mzZvjwAMPjCZNmlT6uT9nzpyYOHFi3HfffZXW+9///d/40Y9+FIMGDYqOHTvuttfBJ+e8v35xzk9ExObNm2PVqlVRUlISjRs3jvz8/Arne+WV3+7Zs2f88Ic/jCRJYsqUKRER8Zvf/CYOPvjguPHGG53/fVJ1lfxRt8p+E5aTk5PcfffdNR63adOm5LHHHkt/I5abm5v06dMnmT17doazZVdYvXp18otf/CL9OlHTpk2TU089NXnhhReSJPn3bzMKCwuTX/7yl8lxxx1X4TcfjRo1So952b5OnTold999d3pPMPYODz30UHoMr7rqqiRJanYV25IlS5If/OAHFf5efOlLX0rvI+M3YnumdevWJRdccEF6zNq2bZuMGjUqvfqhpKQkPf6bNm1KnnrqqWTo0KEVjvO2/51//vnJvHnzXP24l7nlllvSYzhu3LidGvu3v/2twpVwbdu2Ta+kYc9UXFycPPXUU0nv3r3Tq58+//nPJ7///e8r9CssLEz+7//+L/nCF75Q4X2el5e33ed+u3btkquvvjr5xz/+UUevitpw3l+/OOen7LYh5X+u33XXXTtV46233kq+9rWvVfj2xG9/+9uMZlx/CODqmbIfuOPGjUvfTKeffnqyatWqGv/jecOGDcmUKVPSe0M0a9YsufTSS5OVK1dmOXV2gdWrVyf/93//lxxyyCHpB/LJJ5+c/OUvf0mSZOuJ1k9+8pPkc5/7XPr343Of+1xyzjnnJFdffXVy6aWXpjfxLfuvQ4cOyX333ZcUFRXV8aujpv76178m+fn5SU5OTnL00Uen93+ricWLF1c4kW/VqlVy3XXXJYWFhRnOmE/qzTffTC677LIKX0e5+uqrKxz7jRs3Jr/4xS+SY445psJ7vEWLFkleXl7SoEGDCvv/67/+K3nuuecEr3uB8jdjLjt+Rx55ZPLee+/tVJ3nn38+/fp6o0aNki9/+cuCmD1ccXFx8uc//zkNT/Py8pLevXsnf/jDH5Ik2fq5/9Of/rTC537//v2TSy65JLnrrruSH/7wh8m5555b4b3funXr5Ic//GGybNmyOn51VMd5f/3lnJ8kSZIxY8akx++b3/xmur+m7/8ZM2ZUCGiHDx9e6X1jqTkBXD21YMGCpHPnzulvM19++eUkSWp+c90VK1Yk119/fdKmTZv0B3LZb8NcEbFnW716dTJx4sRKP5BffPHF5Oijj05/yP70pz9N5s+fX2H8hg0bkt/85jdJixYt0n4HHHBA8uqrryZJ4vjvDd566600gDv44IOTF198MUmSmr//33777Qr3hvjc5z6X/lbV8d9zFRQUJJdcckl63D71qU8l11xzTXpPmJ/97GfJ4Ycfnj7+9a9/Pbn55puTZ599Nnn22WeT//3f/01v5lv238knn5y8/fbbSZI4EdsblL//Y8uWLZOHH344SZKav/cLCwuT++67L13IoU2bNsnvfve7JEm89/dklYVwhx9+ePKHP/wheeONNyqE7j/72c+Sf/7zn9vVmD59enL44YenV8V16NAheeyxx5Ikcez3Bs776yfn/PVX2TnZzJkzK6xoXn4xlZqct5WUlCQ///nPkw4dOqQ1pk6dmtm86wMBXD318ccfJyeeeGL6Rurdu3d6SXFNf5jOnz+/QiJ+3HHHpTf2Zc9W2Qfyl770pWTw4MHp8fzNb35TYcymTZuSJPn3D+s//elPaYiTk5OT9OvXb7ubtLPnKh+gnX/++en+mr7/Z86cmfznf/5nWuPCCy/MaqrsQtuGcAcddFDygx/8IJk5c2aF9//EiROrvOH6xRdfXCGEGzly5G5+FdRGaWlpUlRUlFx88cVJw4YNk5ycnKRr167J4sWLkySp+Xt/8eLFyfDhw9OvKB122GHpQi7suaoK4cqvcr3tV4vKVsUu+9x/8cUXkx49eqT9u3fvbmGGvYTz/vrLOX/9VlJSkpx88skVzvv+/Oc/12hs2fEvLi5OvvKVr6Q1zjzzzGTTpk0C2FoSwNVjf/rTn9I3UuPGjZOLL754p+/lNH369LTGIYcckrzzzjtZTpldaNsP5CZNmqTHcvLkyVWOK/9344EHHkjHdOrUKXnttdd2x9TZBe66664KIcodd9yRPraj93/5x2699dZ0fIMGDZI//vGPmc6ZXaOyK+E+//nPV/mP8LITrPJXSpS/p1xOTk56FRR7vlmzZlX4h9SJJ56YfpWspifTs2bNSpo1a5ZeBffcc89lOWV2kW1DuPJ/D+67774a1XjiiSfSMU2aNEkef/zxjGfNruK8v/5yzl8/lX2mv/3220n37t3T9/5JJ52UzJkzZ6dqLFiwIL2Srl27dr6C/gkI4Oqpsh+oo0ePTn+YdunSJfnf//3f7Zaors43vvGNtMaECRMymzO73rYfyDk5Ocl3vvOd7X7zta3S0tKktLQ0WbZsWdK/f//0Jq07e3NPdr/yx/TUU09NcnK23mT3s5/9bPLII49U2m9HNU455ZQkJ2fr/aB+/vOfZzJndr1tQ7iy/6q7OXdZCFdUVJTe2Ldhw4bJj370o90xbT6hsvfunXfemR7z/fbbL7nkkkvSq9hqGsKVvxfkTTfdlNmc2bXKQrjDDjssPX6XXXZZja5mKfv7c/rpp6ef+zfccEPWU2YXcN6Pc/76a+PGjcnPfvazpGPHjklOztb7OJ577rnJ3LlzazS+pKQk+fjjj5PevXsnDRs2TBo0aJC88cYbGc9631X1+tPs03L+3/LBX//61+Okk06KiIhFixbF5MmT4/7774/CwsLIyclJl6reke7du6ftdevWZTNhMtGqVas488wz45prrolPfepTkZ+fHyeddFLk5eVFRFS5zHROTk7k5OTE/vvvH126dEn/nmzZsmW3zZ3aycnJiZKSkoiI+O53vxuf//znI0mSmD9/fkyYMCGeeeaZtF9V7//yNc4888xo2LBhbNmyJX7729/Gli1bavRzg7r12c9+Ni677LK4+OKL033Dhw+PM888c4fjGjRoEKWlpZGXlxdf+MIXIiKipKQkpk+fnv6dYM9V9jP9q1/9alxwwQURsfVz+9FHH42bbrop1q5dG7m5uVFaWlpljbL392c+85m03sqVKys8xp6rYcOGMXDgwLjzzjujZ8+eERFx0kknRbNmzaodW3a8DzjggPRYb9y4MbvJsss478c5f/3VpEmTOPXUU+PEE0+MFi1axMaNG+N3v/td3HXXXVFQUJD2q+r9n5ubG23bto0jjjgiSkpKorS0NFavXr27pr/PaVjXE6BuHXHEEXHOOefEokWL4s0330z/EZ4kSZx//vnRtGnTKC0tjdzc7bPasv2HHnpoNGrUKIqLi2PDhg118Cr4JMo+kAsLC+PDDz+MIUOG1GhckiSRk5NT4aS9efPmWU2TXahBgwYREXHkkUfGsGHDYvny5bFkyZL485//HM2aNUvDlbKT8cpOyspqDBgwIPLz82P9+vVRWFgYEVWfxLFn+exnPxvf/va3IyJiwoQJ0b9//2jfvn2Nxubk5MSxxx4bP/7xjyPCifjeplOnTvGNb3wjFi1aFH/6059i2bJl8etf/zoiIn7wgx9Ey5Ytq/zsL/OpT30qmjZtGhs2bEiPv/f+3qFhw4YxYMCAuPXWW+OZZ55JA5nqlH0eNGnSJN1X058Z7Bmc99dvzvnrry5dusT//M//xMcffxzPPPNMrF+/Ph588MEoKiqK//7v/44jjzyyyvP+kpKSaNCgQWzZsiX9pXv5zwF2jgCuHit7gw0dOjT+9a9/xS233BLvv/9+FBQUxC9+8YtYt25dXHbZZbHffvv9/+3dd3hUVfoH8O+dTEgjISRACCUQIBCQoLBIEaUKulJkVRQEBBZEel15EH64SETUUKQsogvuuoJARCkmVIXQSygSekkjhQwlBUhhksz7+4OduxlIQgJTksz38zw83sxt5/recuadc89RL7yCjBdnTk6O2vLBw8PD6sdBT8/T0xNDhgxRK1yFxfthxhYSOp1OvWFXq1bN4mUl83F1dcXQoUMRHR2Nn376CWlpadi8eTNEBHq9Hl26dIGiKEVWxo1fup2dnZGVlQVXV1e2gClnmjVrhlGjRuG5557DyJEjAaDIpKuR8VxISEhQ/27cuPFj7xlUNhjj27lzZ2RkZODu3bs4dOgQEhMTsXr1aty5cwdz586Ft7d3sc+CjIwMNenu5eVlzUMgM9BqtejevTu6dOkCoOTPfQcHByQnJ6vPfSbgyg/W+wlgnd+eNWvWDJ9++ikmTZqEyMhI3Lt3Dz/99BOuX7+OKVOmoEePHup1brxfiAgcHBwQHR2NnTt3Ii8vD23atEGrVq1sfDTlmFVedKUyq2BfL4sWLTLpF6BOnToyfPhwuXnzpsk6BoNBXS82NlZatmwpiqJIYGCgXL161arlJ9sw9hNx8uRJtRPnzp07czSccsYYx+TkZHnnnXfUYeYdHBykR48eJh3rPxxb47qRkZHqiIqDBw+2XuHJrLKzs0XEdKCFohiXmT17tjg4OIiiKPLxxx9btHxkXgX7+lm7dq3JiMaVK1eWbt26SUJCwiPrGGMfGxsr7dq1E0VRpFGjRuwLxg4Yz5moqCh1AI4OHTpITk6OjUtGpcF6P5UW6/wVz6lTp6RXr15SpUoVdVRsX19f+frrryU3N1ddzhj7a9euyahRo8TFxUWcnJxk2rRpkpubW+J+I8kUE3BkcgP99ttvTUbDc3BwkKZNm8q+ffskJSXFZL24uDgZO3aseHt7i6Io8vbbb6ujKVHFZbzZxsXFyZ///GdRFEWqV68uixYtkvz8fN6Myxnj9Z+YmCgDBgxQr2cHBwdp0qSJzJ8//5HljTGOj49XB3KoVauWbN68WURK3pEzlT/G2F68eFG8vLxEURR57rnn5Nq1aybzqewrGKstW7bIa6+9ZjIgR+3atWXNmjVy8eJFk/Xi4uJkzJgxUr16dVEURfr06SOpqanWLj5ZUWH3fC8vL5k3b57o9Xpe9+UM6/1UUqzzV1znz5+X4cOHi6+vr8mzv1+/fvLFF19IYmKiXLp0SQ4cOCC9e/dWB3AICgqSuLg4Wxe/XFNE+L4QweQVsw0bNmD16tXYsmWLOr9q1apo1aoVXnnlFXh6ekKj0WDZsmWIj49HWloaGjRogB07dqBhw4a2OgSyAvlvc+SkpCR8/vnnCA0Nxc2bN9GpUyf8+OOP8PX1tXUR6QkYr/+UlBQEBwdjy5YtSEpKUpueDxo0CIMHD0abNm1QpUoVAMDly5cxf/58hIWFISUlBR07dsT69evh4+Nj46MhSzFe/4mJiZg+fTrWrVsHZ2dnjBw5EnPnzmV/IOWQFHjdeP/+/Vi7di1WrFihzq9cuTJq166NPn36wMPDAy4uLli1ahWSkpJw584d1K9fH7t27eKzvwIreN2HhIQgNDQUOp0OL7zwAtavX4/atWvbuoj0BFjvp8dhnb9sKcmrwqWVlJSEsLAwLF68GBcvXjSZV7VqVeTk5KhdTQAP+o/dvXu3yUAsVHpMwFUQ8pg+e0qi4MP4zJkz2LBhA4KDgx+7XoMGDRAWFobAwMCn2j89OXPE/3HbNv736tWrmDdvHrZt24aUlBTUqVMHv//+OwICAiyyf7IO4/V/+/ZtrF69GqtXr8aJEyfU+b6+vqhatSqeffZZaDQa7NixA3fv3sX9+/dRq1Yt7Nmzh+dABWa8/hMSEhASEoINGzYgJSUFLVu2xMaNG+Hn52frItITKvj8uHXrFn7++Wd8+OGH0Ov10Ov1ha6jKAoaNmyILVu28NlfAT383L9y5Qo+++wzbN++HTqdjvd8Kyt4jT4cm6fBen/ZZ6nYP25/rPOXDZs3b8aOHTuwfPlyAJZJwun1euh0OkyZMgWnTp1CTEyMOs/BwQH5+fnw9fVF06ZNsWLFCjRq1Mis+7dHTMBVME97U354/T179uDrr7/G8ePHERcXZ7JskyZN0KpVKwQHB6NBgwZPvE8yH0s+lPPy8nD48GGMHTsW0dHRyM7ORq1atfDbb7+xElZBGM+fnJwcREVFISQkBD///PMjy2k0GhgMBri4uCAgIADr16/nr2EV0MODb1y4cAGffPIJIiIicOPGDdSsWRMRERFo3LixDUtpHyx5by/MiRMnEBoail9//RVXrlxRO1wHHoye265dO8yYMQP+/v5WK5O9snbsC8rKylKf+/Hx8bh//z78/Pywfft2PvetzGAwICcnB6mpqahduzby8/Oh1WofO1rx47DeX/ZZKvbFYZ3f9rZs2YK+ffsCACZOnIhFixYBMH8SrmDS9cSJE4iIiMDBgwcRHR2NmjVrom7duujbty/atm2LGjVqmG2/9owJuHImLi4O0dHRWLt2Le7evQtXV1dUrlwZffv2RWBgoMmrAOZKxt25cwd3795FWFgY0tPTYTAY4Obmhp49e6J69eocAcmKrBn/gpYvX46IiAiEhYUhJycHDg4OaNWqFVavXs1fwWzAkpWuh33//feIjIzEmjVrkJ+fj3v37kGj0aBdu3bo1KkTPvjgA7Z+siJrxt4oLi4OUVFRGD16NFJSUiAi8Pf3R3h4OCviVpKZmYm0tDT88ssvSE1NhVarhbu7O/r16wdPT091BGJz3PON2zEYDLh37x727t0LnU4Hg8EAJycndO/eHVWqVIGbm5sZjowex5qxL2j+/Pn4/fffsXfvXuTk5MDR0RGtWrXCDz/8wBYQVhQbG4vz589j+fLl0Ol0uH79Oho2bIj27dtj+PDhaNy4sdmeC6z3ly3WjH1BrPPb3rZt29CzZ08AQKVKlaDX6zFu3DgsWbIEgPmTcIWdR3l5edBqtWbbBxVggX7lyEJ2794tL7zwgvj4+Jh0lqgoinh7e4ufn5/8+OOPEhMTo65jjhFq2MFm2WCr+MfHx8uIESPUfQUEBMjgwYPZAacNmDu2xXl4NMy4uDi5evWq7Nu3T44dOyZ5eXmi1+stWgb6H2vG3ig3N1f++c9/SkBAgFSqVEkURRF3d3fp2LEjR76zoqNHj8ro0aPF39//kXt/UFCQTJ8+3SKDYHCEO9uzVezT09Nl1qxZ6r6aNm0qf/3rXyU+Pt5s+6DH27t3r/To0aPQep+jo6PUq1dPTp06JSLmvV5Z77c9W8WedX7by87OlnfffVcURREnJyeT2I8fP15driSj1peW8dp/+JziPcG8mIArJ8LDw9Vh3xVFEVdXV/VvBwcH9XMnJyd588031dEIRViJrghsHf+zZ8/KoEGDpGvXrhIaGiq3b99+6m1S6WzatEmqV68uISEh6me2vrb5QLYOW8X+/v37sm7dOmndurX6hX/SpEmSkJBg8X3TA9u3b5e6deuKi4vLI/d7jUajjkb51ltv8QtSBWPr2N+6dUumT58u3bt3ly1btnCkWysLDw8Xd3d3NeaVK1eWGjVqiLu7u2i1WvVzX19fuXTpkq2LS2Zk69izzm97S5cuFUVRxM3NTVq0aGHVJBxZHl9BLQf279+P3r17486dO/Dz80Pr1q0xbdo0aLVaXLlyBefOncOSJUtw584dAA86TKxTpw4mTZqEiRMnArBMp41kHbaMvxR4rSUpKQmenp587cgGCvYDUa9ePUyePBkTJkwAYJtXEsl6bB37nJwcbN68GYcPH8Ybb7yBli1bwt3d3aL7pAfCw8PRu3dvAA/6XQwMDMTrr7+OSpUq4fr16wgLC8ONGzeQl5cHDw8PDBw4EHPnzoWnp6dtC05PrazEPjMzE1qtFk5OTmbdLhVv69at6NWrFwDA29sbLVu2RHBwMKpVq4Zr165h9+7dWLBgAXJycqDRaDBhwgTMnz8fAFgfKOdsGXvW+csO43ng5OSE4OBgHDx4EJs3b1bnP+3rqPJQtwUP/00WZsvsHz2eTqeT3r17i0ajER8fH5k9e7ZkZGQ8styFCxekf//+4ufnp/46qtFoJDg4WF3mcVlyZtHLnrIQf7Zysq29e/eqv3gaXwOsW7euLF68WF3G1i3hyDLKSuxzc3Mtvg8ytXfvXrUFROPGjeXDDz+Uu3fvmiyzc+dO6d+/vzg6OqqvCkVGRopI6c4LPvvLFsbevkVERKjxb9KkicyaNUvS09NNlrl9+7Z88cUX6nOhY8eOT7Qvxr9sKQuxZ52/bMjIyJAmTZqIo6OjLF++XCIiIqRz585maQlXcNnr16+btdxUMkzAlXFnzpyR2rVri6Io0q1bN7USVrCCZZy+ceOGLFu27JGmqjNnznxk2YcVvBgPHz4st27dssThUCkx/vYtJiZGevbsqb565OzsrMbV3ImYwh7erIjZDmNvvy5duiSdOnUSRVHUH17u3bsnIiJ6vd4k3hEREfKnP/1JPTfef//9Uu2rYOzDw8MlNjbWLMdAT4axt29RUVHSpk0b9T4fHBysxv/h+/zx48fF29tbFEWRZs2aiUjp7tus95UtjD0ZGQwGSU9PV+/v48aNExGR3377TV5++eWnSsIVXGbSpEny9ttvy5kzZ8x/EFQsJuDKuM8++0wURRGtVitr164VkeK/LN27d0+2bdsm7dq1M7lAP/30U3XZ4jpWHDdunLi4uMg333wjaWlpFjgiKg3G3z4ZDAbR6/WybNkyqV69uiiKIjVr1pSpU6eaJFjNlYgpeE6tWrVK9uzZY1IWsh7G3n4Z/38vXrxYjf3rr78ud+7cMZn/8HRISIja8vnFF1+UzMzMUu974sSJoiiKfPTRR+zjzwYYe7p9+7ZMmTJFqlSpIoqiyIgRIwr90bVg/J9//nlRFEXat29f6DaLuoez3le2MPZUmP/7v/8TjUYjXbt2VeuGu3btKjYJl5OTo05nZWUVue1Ro0ap648dO1Yd0IOsgwm4Mm7mzJnqBfKf//xHRB7/pUiv18uBAwekQ4cO6roODg6yZMkSdZnCtjFmzBh1+SZNmsjixYt5Q7Yxxt/+GGMTExMjTZs2FUVRxMPDQxYuXCg3btyQf/zjH9K8eXOLtIaaPHmyKIoiffr0kUOHDj31sVDpMPZ048YNCQwMFEVRpHbt2mpCpLDYGs+XuLg4qVOnjijKg1Fqz58/X6p9jh49Wj2n/Pz8ZOLEiZKYmPj0B0Olwtjbt3379qndiLRs2VKtfxV1Xz927Jj6uuJ3330nZ86ckVWrVsm0adNk/vz5cuTIEZPXF1nvK7sYeyrMsmXL1EE4jPf2vLy8x7aEM667YsUK0el0j2w3Pj5efavCOMrqxIkT5f79+1Y5LmICrsxbuHBhoa8SPk5+fr7s379f2rZtq/46GhAQIGFhYUWuM23aNJO+hoKCgngztjHG3z4ZDAZ55ZVX1Hh07NhR/vjjDxF50Mpx+fLlZk/EfPXVV+r2NBqNdOnSRY4cOWK2Y6KSYezt26RJk0RRHox8NmPGDBF5fEyzs7PV1pHu7u5y8uTJUu3T+Jwx9jcYEBBQaKWdLIuxt18Gg0FmzJghiqJItWrV1PtvYW88GM+JZcuWiaOjozg7O0v37t1Nvowbuy0YOXKk7N6922Q/BbHeZ3uMPT3MGKuoqCipWbOmuLu7m7ydUFQSbtKkSSIismTJEnFzc5Nq1arJnDlzHulDVETkyJEjEhAQoP7Qe/bsWascGz3ABFwZ980336hfirp27SpJSUklfi1Ir9dLeHi4BAUFiaIo4ujoKAMGDCj218158+apFTm+E257jL99ysrKkpkzZ6odbG/atElETF81Nnci5urVq2rCVlEUcXFxkWvXrpnvoKhEGHv7lZeXJ8uXL1eTIREREY9dxxjrt956S43fxo0bS73vlStXqskfVsStj7Gn+Ph4GTZsmEydOrXIRIgx5gcPHhRXV1c17o6OjuLq6iq1atVSW7QYkyvdu3c3+fL+MNb7bI+xp8KkpqaqLZwnT54sIv87D4pKwnXo0EF8fX3VZ8n06dOL3P6BAwekefPmEhUVZZXjof9hAq6M0+l0JgkU45exkn7Bunfvnnz11VdqR/7Ozs5qBa2oRM6XX37Ji7GMYPztV1pamkybNk3mzZunfmYwGCyaiImLi1NfgeIXMdth7O1XRkaGzJ49W/r37y96vb7E602dOlU9F9avX1/i9QqeJ//6179477chxp5u3Lghly5dKnSesUXUqVOnpHLlyqIoinh6ekrz5s1l48aNcvLkSbl48aJERETISy+9pHbS7+joKEOHDpWkpKQi98t6n+0x9lSQMeZ9+/YVRVFkwIAB6jxjXTAvL0927NghPXr0eKQVpKIoMnXq1EfWeVh2drYFj4KKwgRcGZeZmSnvvvuuejH5+Pio74GXtCVUSkqKegEb3/XnsMPlA+Nv3zIzM9VOVAvrhNsSiZj4+HiJiYkxQ+npaTD29isjI0MiIyNLtc6HH374xK2gnnYUXTIfxp6KExkZqbZy8vPzkzFjxkhcXNwjy8XHx8v7778vnp6eamuo4rogobKPsbdPxsH4qlatKnFxcYV+99u/f7/6Oqnxralnn31Wnc8kW9mjAZVprq6umDlzJtzd3QEAqampmDVrFhISEqAoCkSk2PVFBD4+Ppg7d666jYyMDCQnJ1u87PT0GH/75urqChcXFwCAoijq58bYu7m54b333sOYMWPwzDPPAAASExMxf/58LFmyBACg0WhgMBhMtlvceePn5wd/f39zHwqVEmNvvzw8PNC6dWsAxcerIG9vb3U6LS2t0GWM28rLywMA9dzQaFgVLCsYeypKXl4efvjhB+j1etSqVQsDBw7Exx9/jHr16pnc50UEfn5+mDlzJho0aAAAyM3NxbJly5CdnV3i84rKDsbe/hhj1aRJEwAP4piWlqbWBwvG/eDBg7h9+zaAB/d0EUFUVBQmT54MAHB2dkZ+fr41i0+PwSdvOdCsWTPMnj0bzs7OyMvLw759+7B06VLodDqTL2aFURQFBoMBzZo1w7Bhw6AoCnQ6HbZs2WKl0tPTYvypME+aiDEYDFAUBdeuXSvyyxqVbYy9/XjcPd6oSpUq6vS9e/cemS8iUBQFiYmJmDVrFs6ePVtogpbKDsaeCtJqtZg6dSo++ugj9OvXD5MmTYKPjw9ExCSRanw+1KtXD3//+9/h4OAAAEhPT4eLi0uJzysqOxh7+2OMVadOnVCnTh1kZmZi69atAAC9Xq/G/csvv8RXX32l1ulq166tbmPx4sWYMGECAMDBwYFJuDKECbhyYsiQIXjjjTfg6OiIW7duYd26dfj2229x69YtAMX/Umq8SIOCgtTlsrKyLF9oMhvGnwpT2kRMbm4uNBoNzp07h27duuG9995DSkqKLQ+BnhBjTwXl5OSo05UqVTKZZ0zAJCcnY8mSJVi6dClatGiBqKgotoCqABh7++Hn54fp06cjODgYNWrUUONblOrVq6stqW/evInU1FQmXsspxt7+GH809fDwAABcuXIFwP/u8yEhIVi0aBF0Oh0AYOzYsQgNDUX37t3VbSxbtkxtCWdMyJLt8elbTnh5eWHOnDl4/vnn4eDggMTERHz33XdYvny52hKqqCSM8YZbq1YtODk5AXjQlJXKD8afilKSRMzixYsBAI6OjoiKisLw4cORmJiI8PBwjB8/npWycoqxJyNHR0d12nh/lwf9/KoJmAULFmDt2rXIysqCoijq84DKN8bevri7u6Ny5coAim4lafw8PT1dPSdatGgBLy8vJl7LMcbevmg0Gnh5eeHVV18FABw/fhyZmZkAHrR8W7hwoZp8GzduHJYuXYq2bdtiypQp6NatG4AHz4fFixdj+vTptjkIKpTW1gWgkmvQoAFWrlyJfv364eLFi4iPj8fKlSuRkZGBiRMnws/PDwaD4ZEbrPFmnJWVBb1eDwDw9PS0dvHpKTH+VJSHEzEAsHz5cpw7dw6JiYlYsGAB3N3d0alTJ4wcORKnTp1Cbm4uvL298fHHH7NSVo4x9gRA/XJlMBiQmpoKAOrrScYETGhoKJKSkuDl5YUDBw6ofctQ+cbY08OMdcGYmBi13hcQEGDjUpE1MPYVj4+PDwAgOTkZOp0O27ZtM2n5Nn78ePXHVgB4+eWXodVqodVqsWPHDnh6emLIkCE2KTsVwfzjOpClnTlzRoKCgsTR0VEURRFvb2/p06ePnDt3zmS5/Px8dYSr2NhYad++vSiKIgEBAXL69GlbFJ3MgPGnohQ3QmbNmjXFz89PKlWqpJ43xhF1qfxj7O3bmjVr1Hh/8skn6udJSUkyZcoUqVOnjhr7Cxcu2LCkZG6MPRVkfBZcuHBBfH19RVEUee655yQ2NtZkPlU8jH3FFBkZKdWqVRNXV1d58cUXpWbNmuo9f8KECepyeXl5JtNbt26Vvn37ytmzZ21RbCoGf/ouh5o3b47Q0FC0a9cOjo6OSE1NRVhYGF566SWEhoYiNjYWwIOmqxqNBrGxsQgJCcHVq1cBAM888wz8/PxseQj0FBh/KkrB1lCDBw/GqFGj0KJFCwCATqeDTqdDbm4uvLy8sH//fjRt2tTGJSZzYeztk/y364GC3QoYP0tISHik9dP+/fsRGBhok7KSeTH29DD572vHCQkJmDNnDm7cuAFXV1d069YN1atXB1DywT2ofGHsK64aNWpAURRkZ2cjKiqq0JZv+fn5Jn28OTg4oEePHlizZo3aNQmVHXwFtZwKDAzE999/jzlz5iA0NBTZ2dlIS0vDoEGD0LJlS7zwwgvw9fWFVqvFypUrcf36dWRkZMDf3x8LFizgK4jlHONPRTGOfFu5cmWMHTsWKSkpuHLlCvLz86HX61G1alUmYCooxt7+GL9QValSxWRkS51Oh4ULF2LDhg0mCRjGvuJg7KmgggmYkJAQ7NmzBwaDAc2aNcPEiRPh5uZm6yKShTD2FVvdunUxZcoUfP7557hz5w6A4pNvRg4ODnB1dbVqWalkFJFihk+kMi8tLQ1r167FjBkz1IuysA75FUVBQEAANm/ezL4/KhDGnwpj7APk6tWr6N+/P86cOYPc3FxUrVoVBw4c4BexCoyxt0/btm1Dnz59kJ+fj7/85S9o1KgRfvzxR5N+v9j6qWJi7O2XMfFi/O/ly5cxd+5c7Nq1CykpKahVqxb27NnDPsAqIMbevqSlpWHhwoWYO3cuRo4ciRUrVgAoOvlGZRsTcBXEpUuXsGjRIhw/fhwnT540mRcUFITWrVtj1qxZqF+/vm0KSBbF+JORMQFz7tw5DBs2DKdPn2YCxk4w9vZry5YteOONNwAA1apVg1arRXJyMls/2QHGnjIzM3Hs2DGMHj0a8fHxuH//PmrWrIndu3cz+VrBMfb2Iy0tDYcOHULPnj0BMPlWnjEBV4Hcv38fubm52LFjBzIzM5GdnQ1nZ2f06NEDHh4ebIJcwTH+ZHT27FmMGDECf/zxB/R6Pb+I2RHG3j7t2rULPXv2hMFggFarVWPP1k8VH2Nvv/Ly8vD1118jPDwce/fuxf379+Hs7IygoCCsXr2arZ8qMMbevjH5Vr6xD7gKxMnJCU5OTnjzzTdtXRSyAcafgAcdcn/++ec4duwYADABY0cYe/tVtWpVODo6Ijs726S/PyZgKj7G3n5lZmbi3Llz2LdvH+7fv49nnnkGXbp0wbRp01CnTh1bF48siLG3b0y+lW9sAUdEVMFcvXoV3bp1Q2pqKo4dO8YEjB1h7O1Tamoq/va3v+Hf//43XF1dERkZydjbCcbevt28eRMzZ85Eeno6Ro8ejVatWqFKlSq2LhZZAWNPVD4xAUdEVAHFxMRAURT4+/vbuihkZYy9fUpMTMS8efMwfvx4tn6yM4y9fcvMzGQ3I3aKsScqf5iAIyIiIqoA8vLyoNWydxF7xNiTcURMsj+MPVH5wQQcERERERERERGRBWlsXQAiIiIiIiIiIqKKjAk4IiIiIiIiIiIiC2ICjoiIiIiIiIiIyIKYgCMiIiIiIiIiIrIgJuCIiIiIiIiIiIgsiAk4IiIiIiIiIiIiC2ICjoiIiIiIiIiIyIKYgCMiIiIiIiIiIrIgJuCIiIiIiIiIiIgsiAk4IiIiIiIiIiIiC2ICjoiIiIiIiIiIyIKYgCMiIiIiIiIiIrIgJuCIiIiIiIiIiMqp/Px8REVFYdWqVRg9ejRat26NSpUqQVEUKIqCzp0727qIVjV06FD12Ev6b/Xq1RYvl9bieyAiIiIiIiIiIrPbtGkTBg4ciKysLFsXhR6DCTgiIiIiIiIionIoPT2dybdidOvWDYGBgY9drkmTJhYvCxNwRERERERERETlmI+PD55//nn1344dO7B48WJbF8vmBg0ahKFDh9q6GACYgCMiIiIiIiIiKpdeffVVxMfHw8/Pz+Tzo0eP2qhEVBQm4IiIiIiIiIiIyqGaNWvaughUQhwFlYiIiIiIiIiITOTm5uKHH37A22+/jQYNGsDd3R1ubm7w9/fHgAEDsHHjRoiIrYtZbrAFHBERERERERERqSIiIjBixAhER0c/Mi8uLg5xcXFYt24d2rVrhw0bNqB27do2KGX5wgQcEREREREREREBAH766ScMHDgQubm5AAAXFxe0a9cO9evXh0ajweXLl3H48GHk5eXhyJEjaN++PSIjI+Hj42Pjkj8qPj4eq1atQkxMDLKzs+Hl5QV/f3+89NJLj/SbZ2lMwBEREREREREREc6dO4chQ4YgNzcXiqJg6tSpmDlzJjw9PU2Wi4mJwZAhQ3DgwAEkJCRg2LBh2Lp1q20KXYzZs2cXOa9z586YPXs2OnXqZJWysA84IiIiIiIiIiLChAkTkJ2dDQBYsGABQkJCHkm+AUCDBg2wfft2NGvWDACwbdu2cjfyakREBLp27Vpsks6cmIAjIiIiIiIiIrJzp0+fxu7duwEALVu2xKRJk4pd3s3NDbNmzVL/XrNmjSWLV2KKoqB169aYO3cu9u/fj5s3byI3Nxfp6emIjIzE3//+d3h7ewMADAYDPvnkE8yfP9/i5eIrqEREREREREREdq7gK6QDBgyAoiiPXadr167q9IEDByxSrtKaP3++mmArqEqVKmjdujVat26NDz74AH369MHx48cBADNmzMCbb74Jf39/i5WLCTgiIiIiIiIiIjt3+PBhdXrPnj2Ij49/7Doiok4nJCQUusx7772HY8eOPX0BC9i5c2eRgygUlnx7mK+vL8LDwxEYGIi0tDTk5uZi4cKFWLp0qVnLWRATcEREREREREREdi45OVmd3rZtW6nXT0tLK/Tza9eu4dKlS09crsLo9fqn3kaNGjUwduxYfPrppwCe7JhLg33AERERERERERHZuYyMjKdaPz8/30wlsZ6XX35ZnY6OjjZLYq8oTMAREREREREREdk5Nzc3dfqXX36BiJT6X2EiIiKeaFvF/WvUqJFZjtnX19fk79u3b5tlu4VhAo6IiIiIiIiIyM75+Pio0ykpKTYsifVkZmaa/F0wCWluTMAREREREREREdm5tm3bqtMHDx60YUms59SpU+q0m5sbPDw8LLYvJuCIiIiIiIiIiOxcr1691OlffvkFOp3OhqWxju+++06d7ty5s0X3xQQcEREREREREZGda9OmjZqEys7OxuDBg0s8KIFery9yFFRrunfvXomXXbhwoUlLv0GDBlmiSCom4IiIiIiIiIiICEuXLkXlypUBALt27ULHjh1x9OjRIpe/fPkygoODUb9+/TLx2uqECRPw1ltvYfv27cjNzS10GZ1OhzFjxmDq1KnqZ+3atcM777xj0bIpUtQwFUREREREREREVKa99tprSE5ONvksJSVFfYXUzc2t0FFDt27dilq1aj3yeVhYGN555x1kZWWpnzVs2BCtWrWCl5cXcnJycOPGDURFRSEpKUld5tdffzV5jdUWhg4diu+//x7Ag+MOCgqCv78/PDw8kJ2djatXryIyMtIkOdewYUMcPHjQZBAKS9BadOtERERERERERGQx58+fR3x8fJHzMzMzcfr06Uc+L+r10l69euHQoUMYPnw4Tpw4AQCIjo5GdHR0kfuoX78+6tSpU8qSW1ZmZiaOHDmCI0eOFDpfo9FgwIABWLZsGTw9PS1eHraAIyIiIiIiIiIqp+rXr19sAq4osbGxqF+/frHL7Ny5E5s2bcLBgweRnJyM9PR0ODk5oXr16mjSpAnatm2LV155Be3bt4eiKE94BOaTnp6Ow4cP4/Dhwzh69CiSkpJw+/ZtpKamQqvVomrVqmjatCk6dOiAwYMHo2HDhlYrGxNwREREREREREREFsRBGIiIiIiIiIiIiCyICTgiIiIiIiIiIiILYgKOiIiIiIiIiIjIgpiAIyIiIiIiIiIisiAm4IiIiIiIiIiIiCyICTgiIiIiIiIiIiILYgKOiIiIiIiIiIjIgpiAIyIiIiIiIiIisiAm4IiIiIiIiIiIiCyICTgiIiIiIiIiIiILYgKOiIiIiIiIiIjIgpiAIyIiIiIiIiIisiAm4IiIiIiIiIiIiCyICTgiIiIiIiIiIiILYgKOiIiIiIiIiIjIgpiAIyIiIiIiIiIisiAm4IiIiIiIiIiIiCyICTgiIiIiIiIiIiILYgKOiIiIiIiIiIjIgpiAIyIiIiIiIiIisiAm4IiIiIiIiIiIiCyICTgiIiIiIiIiIiILYgKOiIiIiIiIiIjIgpiAIyIiIiIiIiIisiAm4IiIiIiIiIiIiCzo/wGOldugvZHz3gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 463,
       "width": 624
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f = op.models.geometry.pore_seed.random\n",
    "pn.add_model(propname='pore.seed',\n",
    "             model=f,\n",
    "             num_range=[0.0, 0.98])\n",
    "pn.add_model(propname='pore.diameter',\n",
    "             model=op.models.geometry.pore_size.generic_distribution,\n",
    "             func=dst,\n",
    "             seeds='pore.seed')\n",
    "pn.regenerate_models()\n",
    "fig, ax = plt.subplots()\n",
    "ax.hist(pn['pore.diameter'], edgecolor='k')\n",
    "ax.tick_params(axis='x', labelrotation=45);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Throat Sizes\n",
    "\n",
    "When assigning throat sizes it must be remembered that throat sizes should *usually* be smaller than the two pores which they connect.  This is not *strictly* necessary, but it is consistent with the general picture of a porous material, and it also make other calculations quite a bit simpler. \n",
    "|\n",
    "There are two methods we can use to assign throat sizes. We can assume that each throat is smaller than the two pores it connects by some factor, i.e., `0.5 * min(d1, d2)`.  Alternatively, we can assign each throat a `seed` value, which is taken as the minimum of the seed value in the two pores it connects, then use those values in any desired size distribution (which should produce smaller values than the chosen pore size distribution given the same seed values).\n",
    "\n",
    "Let's do both:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 343,
   "metadata": {},
   "outputs": [],
   "source": [
    "pn.add_model(propname='throat.diameter_1', \n",
    "             model=op.models.misc.from_neighbor_pores,\n",
    "             prop='pore.diameter',\n",
    "             mode='min')\n",
    "pn.add_model(propname='throat.seed', \n",
    "             model=op.models.misc.from_neighbor_pores,\n",
    "             prop='pore.seed',\n",
    "             mode='min')\n",
    "pn.add_model(propname='throat.diameter_2',\n",
    "             model=op.models.geometry.throat_size.generic_distribution,\n",
    "             func=dst)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And we can choose which of these becomes the \"official\" throat diameter, and apply some scaling to the values if needed using:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 344,
   "metadata": {},
   "outputs": [],
   "source": [
    "pn.add_model(propname='throat.diameter',\n",
    "             model=op.models.misc.scaled,\n",
    "             prop='throat.diameter_1',  # This could also be 'throat.diameter_2'\n",
    "             factor=0.6,  # This could be 1.0 if no scaling is desired\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's plot the two distributions together:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 345,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 463,
       "width": 623
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.hist(pn['pore.diameter']*1e6, edgecolor='k', density=True, alpha=0.5, label='pores')\n",
    "ax.hist(pn['throat.diameter']*1e6, edgecolor='k', density=True, alpha=0.5, label='throats')\n",
    "ax.tick_params(axis='x', labelrotation=45)\n",
    "ax.legend()\n",
    "ax.set_xlabel('Pore diameter [um]');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To fully define the geometry for this network we need to assign pore and throat volumes.  This requires making an assumption about their shapes, since spheres and cubes have different volumes. Let's assume spherical pores:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 346,
   "metadata": {},
   "outputs": [],
   "source": [
    "pn.add_model(propname='pore.volume',\n",
    "             model=op.models.geometry.pore_volume.sphere)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To compute the throat volume we need to know not only the diameter but also the length.  Things get a bit nuanced here because of the way that spherical pore bodies and cylindrical throat overlap.  There is a 'lens' shaped region of overlap whose volume will be counted twice.  So the following set of models is necessary: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 347,
   "metadata": {},
   "outputs": [],
   "source": [
    "pn.add_model(propname='throat.length',\n",
    "             model=op.models.geometry.throat_length.spheres_and_cylinders)\n",
    "pn.add_model(propname='throat.total_volume',\n",
    "             model=op.models.geometry.throat_volume.cylinder)\n",
    "pn.add_model(propname='throat.lens_volume', \n",
    "            model=op.models.geometry.throat_volume.lens)\n",
    "pn.add_model(propname='throat.volume', \n",
    "             model=op.models.misc.difference,\n",
    "             props=['throat.total_volume', 'throat.lens_volume'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Phase\n",
    "\n",
    "Next we create a phase object which contains the thermophysical properties of the invading fluid, such as surface tension. In the case of mercury intrusion, the invading fluid is of course mercury!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 348,
   "metadata": {},
   "outputs": [],
   "source": [
    "hg = op.phase.Mercury(network=pn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add Physics\n",
    "\n",
    "To simulate mercury intrusion, we will need to calculate the capillary pressure of the throats in the network. The capillary pressure can be calculated using the Washburn equation as provided below.\n",
    "\n",
    "$$ P_C = \\frac{-2\\sigma cos(\\theta)}{R_T} $$\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 349,
   "metadata": {},
   "outputs": [],
   "source": [
    "hg.add_model(propname='throat.entry_pressure',\n",
    "             model=op.models.physics.capillary_pressure.washburn)\n",
    "hg.regenerate_models()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The washburn model will fetch the surface tension and contact angle from the mercury phase object while the throat radius is fetched from the network object. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Perform Mercury Intrusion\n",
    "\n",
    "Now that all the required objects and models are setup, we can perform the capillary pressure curve simulation.  The mercury intrusion experiment is a \"drainage\" since the wetting fluid (i.e. rarefied air) is being 'drained' while the non-wetting fluid is invading.  \n",
    "\n",
    "When setting the boundary conditions for this simulation all the surface pores should be considered as inlets since the experiment starts with the sample fully surrounded by mercury.  The ``Cubic`` class has a `'pore.surface'` label which we can use:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4677df7856724b50a45b4a88b2d5c78d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Performing drainage simulation:   0%|          | 0/25 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mip = op.algorithms.Drainage(network=pn, phase=hg)\n",
    "mip.set_inlet_BC(pores=pn.pores('surface'))\n",
    "mip.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's compare the simulation to the experimental data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 463,
       "width": 623
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pc_sim = mip.pc_curve()\n",
    "fig, ax = plt.subplots()\n",
    "ax.semilogx(*pc_sim, 'b-', label='simulation')\n",
    "ax.semilogx(df['Pc [Pa]'], df['S_Hg'], 'r.', label='experiment')\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The agreement is surprisingly good for a first guess.  We probably want to make the throat sizes in the network a little bit larger to shift the curve left.  Recall that to compute the throat sizes we took the minimum size of the two neighboring pores and scaled it by 0.5. Let's adjust this scale factor.  We could readd a new model over the old one, or just adjust the stored parameters of the current one:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 352,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d40b784d616645a8bbb6f9c471357b39",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Performing drainage simulation:   0%|          | 0/25 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 463,
       "width": 623
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pn.models['throat.diameter@all']['factor'] = 0.9\n",
    "pn.regenerate_models()\n",
    "hg.regenerate_models()\n",
    "mip = op.algorithms.Drainage(network=pn, phase=hg)\n",
    "mip.set_inlet_BC(pores=pn.pores('surface'))\n",
    "mip.run()\n",
    "pc_sim = mip.pc_curve()\n",
    "fig, ax = plt.subplots()\n",
    "ax.semilogx(*pc_sim, 'b-', label='simulation')\n",
    "ax.semilogx(df['Pc [Pa]'], df['S_Hg'], 'r.', label='experiment')\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This helped quite a bit, but is still not great.  \n",
    "\n",
    "The process of adjusting the pore and throat size distributions to match MIP curves has been studied by many people over the years in attempts to automate it.  OpenPNM does not have any automated algorithms for this (at least not at the moment), so we must forge ahead by hand.  The next thing to try would be to shift the pore size distributions to slightly higher values. We can play with the `c` value which is the skewness of the curve, and we can adjust the `scale` which shifts it to higher sizes.\n",
    "\n",
    "Let's plot a new distribution on top of the current values on the network to see how things will change:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 353,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 463,
       "width": 623
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dst = spst.weibull_min(c=2.2, loc=1e-7, scale=22e-6)\n",
    "fig, ax = plt.subplots()\n",
    "ax.hist(dst.rvs(10000)*1e6, bins=50, edgecolor='k', density=True, alpha=0.5)\n",
    "ax.hist(pn['pore.diameter']*1e6, bins=50, edgecolor='k', density=True, alpha=0.5)\n",
    "ax.tick_params(axis='x', labelrotation=45)\n",
    "ax.set_xlabel('Pore Diameter [um]');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since the new distribution looks like an improvement, let's add it to the network and repeat:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 354,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4a6d13917cab408ea0fa085a1a07998b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Performing drainage simulation:   0%|          | 0/25 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 463,
       "width": 623
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pn.models['pore.diameter@all']['func'] = dst\n",
    "pn.regenerate_models()\n",
    "hg.regenerate_models()\n",
    "mip = op.algorithms.Drainage(network=pn, phase=hg)\n",
    "mip.set_inlet_BC(pores=pn.pores('surface'))\n",
    "mip.run()\n",
    "pc_sim = mip.pc_curve()\n",
    "fig, ax = plt.subplots()\n",
    "ax.semilogx(*pc_sim, 'b-', label='simulation')\n",
    "ax.semilogx(df['Pc [Pa]'], df['S_Hg'], 'r.', label='experiment')\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now teh fit in the low pressure region is nearly perfect. Of course the high pressure region is not fitting at all, but as discussed by Tsakiroglou and Payatakes in their paper, this sandstone has a dual porosity or microporosity, which is not resolved by the basic network used here.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Check Geometric Consistency\n",
    "\n",
    "We used a spacing of 40 um when creating the network, but we have some pores which are greater than 30 um in diameter.  If two of these pores happen to be beside each other, then geometric 'inconsistencies' will arise.  For instance, the throat volume might have some negative values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 360,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4.098593686530963e-05\n",
      "-1.174072534598329e-14\n"
     ]
    }
   ],
   "source": [
    "print(pn['pore.diameter'].max())\n",
    "print(pn['throat.volume'].min())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To remedy this we can increase the lattice spacing of the network. Instead of creating an entirely new network, this can be done simply by scaling the pore coordinates directly.  We will scale the spacing to 50 um instead of 30 um, by multiplying all the coordinates by 50/30:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 361,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1ea5c30d332e421c9dff768a9be05846",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Performing drainage simulation:   0%|          | 0/25 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 463,
       "width": 623
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pn['pore.coords'] *= 50/30\n",
    "pn.regenerate_models()\n",
    "hg.regenerate_models()\n",
    "mip = op.algorithms.Drainage(network=pn, phase=hg)\n",
    "mip.set_inlet_BC(pores=pn.pores('surface'))\n",
    "mip.run()\n",
    "pc_sim = mip.pc_curve()\n",
    "fig, ax = plt.subplots()\n",
    "ax.semilogx(*pc_sim, 'b-', label='simulation')\n",
    "ax.semilogx(df['Pc [Pa]'], df['S_Hg'], 'r.', label='experiment')\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The capillary pressure curve was not changed noticeably because the only thing that changed is the throat lengths (not sizes).  This adjustment has fixed the problem of negative throat lengths:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 362,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9.000494059369823e-18"
      ]
     },
     "execution_count": 362,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pn['throat.volume'].min()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Additional Calibration Steps\n",
    "\n",
    "We could also check the permeability coefficient, formation factor (i.e. tortuosity), and porosity to ensure they also match, but this would require yet more iterating to find a suitable set of pore and throat sizes.\n",
    "\n",
    "For instance, in the present case we can find the network porosity using:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 364,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.1687368766069287"
      ]
     },
     "execution_count": 364,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(pn['pore.volume'].sum() + pn['throat.volume'].sum())/(15**3 * (50e-6)**3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This value is only slightly below the known value of 0.18.  This means the pores are spaced too far apart.  Instead of 50 um spacing, perhaps 48 um would have been better."
   ]
  }
 ],
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